huihui-ai

This is an uncensored version of Qwen2.5-32B-Instruct created with abliteration (see this article to know more about it). Special thanks to @FailSpy for the original code and technique. Please follow him if you're interested in abliterated models. You can use huihuiai/qwen2.5-abliterate:32b directly, Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library:

This is an uncensored version of Qwen/Qwen3-VL-8B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not...

This is an uncensored version of Qwen/Qwen3-VL-32B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. The abliterated model will no longer say "I can’t describe or analyze this image." ollama Please update to the latest version of Ollama-v0.12.7. You can use huihuiai/qwen3-vl-abliterated:32b-instruct directly, The official llama.cpp-b6907 has now been updated to support Qwen3-VL conversion to GGUF format and can be tested using llama-mtmd-cli. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

huihui-ai/Huihui-Qwen3-VL-30B-A3B-Instruct-abliterated This is an uncensored version of Qwen/Qwen3-VL-30B-A3B-Instruct created with abliteration (see remove-refusals-with-transformers to know more ...

This is an uncensored version of unsloth/gpt-oss-20b-BF16 created with abliteration (see remove-refusals-with-transformers to know more about it). New Version: huihui-ai/Huihui-gpt-oss-20b-BF16-abliterated-v2 llama.cpp-b6115 now supports conversion to GGUF format and can be tested using llama-cli. Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin: - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

This is an uncensored version of Qwen/Qwen3-VL-32B-Thinking created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. The abliterated model will no longer say "I can’t describe or analyze this image." UGI Leaderboard This model now tops the UGI Leaderboard with a perfect score in the W10 category. Meaning that it's the first model to not refuse to answer or to deviate from an unsafe instruction at all. ollama Please update to the latest version of Ollama-v0.12.7. You can use huihuiai/qwen3-vl-abliterated:32b directly, The official llama.cpp-b6907 has now been updated to support Qwen3-VL conversion to GGUF format and can be tested using llama-mtmd-cli. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of unsloth/gpt-oss-120b-BF16 created with abliteration (see remove-refusals-with-transformers to know more about it). You can use huihuiai/gpt-oss-abliterated:120b directly, Use the llama.cpp split program to merge model (llama-gguf-split needs to be compiled.), If you use llama-cli to run GGUF, it is recommended to use the latest version of llama.cpp. Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin: - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

This is an uncensored version of Qwen/Qwen3-VL-4B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. The abliterated model will no longer say "I can’t describe or analyze this image." ollama Please update to the latest version of Ollama-v0.12.7. You can use huihuiai/qwen3-vl-abliterated:4b-instruct directly, The official llama.cpp-b6907 has now been updated to support Qwen3-VL conversion to GGUF format and can be tested using llama-mtmd-cli. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This model is a fine-tuned version of huihui-ai/Huihui-gpt-oss-20b-BF16-abliterated. It has been trained using TRL. Please refer to Quantization-Aware Training (QAT) for fine-tuning and quantization(huihui-ai/Huihui-gpt-oss-20b-mxfp4-abliterated-v2). Dataset Using huihui-ai/Huihui-gpt-oss-20b-BF16-abliterated to generate a dataset for harmful instructions. Advantages: All core metrics (Loss/Acc/Entropy) improve synchronously, with a small gap between Eval and Train (<0.01), indicating strong generalization ability. Fine-tuning shows effect in just 400 steps, with high efficiency. Potential Issues: The rise in Grad Norm in the later stages may be caused by lack of learning rate decay or batch noise; suggest checking the logs for signs of gradient explosion. You can use huihuiai/gpt-oss-abliterated:20b-v2-q4KM directly, llama.cpp-b6115 now supports conversion to GGUF format and can be tested using llama-cli. - TRL: 0.23.0 - Transformers: 4.57.0.dev0 - Pytorch: 2.8.0+cu128 - Datasets: 4.0.0 - Tokenizers: 0.22.0 - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin（BTC): - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

This is an uncensored version of inclusionAI/Ling-mini-2.0 created with abliteration (see remove-refusals-with-transformers to know more about it). ggml-org/llama.cpp and im0qianqian/llama.cpp now supports conversion to GGUF format and can be tested using llama-cli. Q4KM may sometimes refuse to respond; it is recommended to use Q80 or f16 instead. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of Qwen/Qwen3-VL-8B-Thinking created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. The abliterated model will no longer say "I can’t describe or analyze this image." ollama Please update to the latest version of Ollama-v0.12.7. You can use huihuiai/qwen3-vl-abliterated:8b directly, The official llama.cpp-b6907 has now been updated to support Qwen3-VL conversion to GGUF format and can be tested using llama-mtmd-cli. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of Qwen/Qwen3-VL-4B-Thinking created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. The abliterated model will no longer say "I can’t describe or analyze this image." ollama Please update to the latest version of Ollama-v0.12.7. You can use huihuiai/qwen3-vl-abliterated:4b directly, llama.cpp.tr-qwen3-vl-6-b7106-495c611 now supports conversion to GGUF format and can be tested using llama-mtmd-cli. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of Qwen/Qwen3-VL-2B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. The abliterated model will no longer say "I can’t describe or analyze this image." ollama Please update to the latest version of Ollama-v0.12.7. You can use huihuiai/qwen3-vl-abliterated:2b-instruct directly, The official llama.cpp-b6907 has now been updated to support Qwen3-VL conversion to GGUF format and can be tested using llama-mtmd-cli. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is a mxfp4 version of huihui-ai/Huihui-gpt-oss-20b-BF16-abliterated-v2 Reference OpenAI GPT-OSS Quantization Aware Training (QAT) & Quantized Deployment You can use huihuiai/gpt-oss-abliterated:20b-mxfp4 directly, llama.cpp-b6115 now supports conversion to GGUF format and can be tested using llama-cli. Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin: - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

This is an uncensored version of Qwen/Qwen3-8B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. Ablation was performed using a new and faster method, which yields better results. Important Note This version is an improvement over the previous one huihui-ai/Qwen3-8B-abliterated. The ollama version has also been modified. Changed the 0 layer to eliminate the problem of garbled codes You can use huihuiai/qwen3-abliterated:8b-v2 directly, Switch the thinking toggle using /set think and /set nothink Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin（BTC):

huihui-ai/Huihui-Qwen3-VL-235B-A22B-Instruct-abliterated-GGUF This is an uncensored version of Qwen/Qwen3-VL-235B-A22B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. The abliterated model will no longer say "I can’t describe or analyze this image." The official llama.cpp-b6907 has now been updated to support Qwen3-VL conversion to GGUF format and can be tested using llama-mtmd-cli. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of zai-org/GLM-4.5-Air created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. Use the llama.cpp split program to merge model (llama-gguf-split needs to be compiled.), - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin（BTC): - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

huihui-ai/Huihui-Qwen3-4B-Instruct-2507-abliterated This is an uncensored version of Qwen/Qwen3-4B-Instruct-2507 created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. Ablation was performed using a new and faster method, which yields better results. You can use huihuiai/qwen3-abliterated:4b-instruct-2507-q4KM directly, Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin（BTC): - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

This is an uncensored version of zai-org/GLM-4.5-Air created with abliteration (see remove-refusals-with-transformers to know more about it). This is just the MLX model we generated under Linux using mlx-lm version 0.28.1.; it hasn’t been tested in an Apple environment. If there are any issues, please let us know. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin（BTC): - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

This is an uncensored version of Qwen/Qwen3-VL-2B-Thinking created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. The abliterated model will no longer say "I can’t describe or analyze this image." The model has been updated, and the results when testing gguf are not very good. Those who have already downloaded the file can download it again. ollama Please update to the latest version of Ollama-v0.12.7. You can use huihuiai/qwen3-vl-abliterated:2b directly, The official llama.cpp-b6907 has now been updated to support Qwen3-VL conversion to GGUF format and can be tested using llama-mtmd-cli. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

huihui-ai/Llama-3.3-70B-Instruct-abliterated This is an uncensored version of meta-llama/Llama-3.3-70B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. If you don't get the result you want, you can try the same question again. You can use huihuiai/llama3.3-abliterated directly, Starting with `transformers >= 4.43.0` onward, you can run conversational inference using the Transformers `pipeline` abstraction or by leveraging the Auto classes with the `generate()` function. Make sure to update your transformers installation via `pip install --upgrade transformers`.

huihui-ai/Huihui-Qwen3-30B-A3B-Instruct-2507-abliterated This is an uncensored version of Qwen/Qwen3-30B-A3B-Instruct-2507 created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. Ablation was performed using a new and faster method, which yields better results. You can use huihuiai/qwen3-abliterated:30b-a3b-instruct-2507-q4KM directly, Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin（BTC):

This is an uncensored version of Qwen/Qwen2.5-VL-3B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. You can use huihuiai/qwen2.5-vl-abliterated:3b directly, The official llama.cpp-b6907 has now been updated to support Qwen2.5-VL conversion to GGUF format and can be tested using llama-mtmd-cli. Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

huihui-ai/Mistral-Small-24B-Instruct-2501-abliterated This is an uncensored version of mistralai/Mistral-Small-24B-Instruct-2501 created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. You can use huihuiai/mistral-small-abliterated directly

This is an uncensored version of Qwen2.5-3B-Instruct created with abliteration (see this article to know more about it). Special thanks to @FailSpy for the original code and technique. Please follow him if you're interested in abliterated models. You can use huihuiai/qwen2.5-abliterate:3b directly, Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library:

This is an uncensored version of inclusionAI/Ring-mini-2.0 created with abliteration (see remove-refusals-with-transformers to know more about it). ggml-org/llama.cpp and im0qianqian/llama.cpp now supports conversion to GGUF format and can be tested using llama-cli. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated This is an uncensored version of Qwen/Qwen3-4B-Thinking-2507 created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. Ablation was performed using a new and faster method, which yields better results. You can use huihuiai/qwen3-abliterated:4b-thinking-2507-q4KM directly, Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin（BTC): - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

This is an uncensored version of deepseek-ai/DeepSeek-R1-Distill-Qwen-32B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. If "\ " does not appear or refuses to respond, you can first provide an example to guide, and then ask your question. For instance: You can use huihuiai/deepseek-r1-abliterated directly Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of Qwen/Qwen2.5-VL-7B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. You can use huihuiai/qwen2.5-vl-abliterated:7b directly, Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

huihui-ai/Huihui-Qwen3-Coder-30B-A3B-Instruct-abliterated This is an uncensored version of Qwen/Qwen3-Coder-30B-A3B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. Ablation was performed using a new and faster method, which yields better results. You can use huihuiai/qwen3-coder-abliterated directly, Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin（BTC):

This is an uncensored version of inclusionAI/Ling-flash-2.0 created with abliteration (see remove-refusals-with-transformers to know more about it). ggml-org/llama.cpp and im0qianqian/llama.cpp now supports conversion to GGUF format and can be tested using llama-cli. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of zai-org/GLM-4.5V created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. The abliterated model will no longer say "I cannot describe this image ..." - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin: - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

huihui-ai/Huihui-Qwen3-Omni-30B-A3B-Instruct-abliterated This is an uncensored version of Qwen/Qwen3-Omni-30B-A3B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of internlm/internlm3-8b-instruct created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. You can use huihuiai/internlm3-abliterated directly

This is an uncensored version of ibm-granite/granite-4.0-h-micro created with abliteration (see remove-refusals-with-transformers to know more about it). Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin: - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

This is an uncensored version of ibm-granite/granite-4.0-h-tiny created with abliteration (see remove-refusals-with-transformers to know more about it). Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin: - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

This is an uncensored version of ibm-granite/granite-4.0-micro created with abliteration (see remove-refusals-with-transformers to know more about it). Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin: - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

This is an uncensored version of deepseek-ai/DeepSeek-R1-Distill-Llama-8B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. If "\ " does not appear or refuses to respond, you can first provide an example to guide, and then ask your question. For instance: You can use huihuiai/deepseek-r1-abliterated directly Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of Qwen/Qwen3-0.6B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. Ablation was performed using a new and faster method, which yields better results. Important Note This version is an improvement over the previous one huihui-ai/Qwen3-0.6B-abliterated. The ollama version has also been modified. Changed 0 layer to eliminate the problem of garbled codes You can use huihuiai/qwen3-abliterated:0.6b-v2 directly, Switch the thinking toggle using /set think and /set nothink Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin（BTC):

This is an uncensored version of microsoft/phi-4 created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. Use with ollama Note: this model requires Ollama 0.5.5

This is an uncensored version of google/gemma-3-12b-it created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. It was only the text part that was processed, not the image part. The abliterated model will no longer say "I'm programmed to be a safe and helpful AI assistant. I cannot fulfill your request to ..." Use with ollama Ollama supports multimodal (Vision). gemma-3-abliterated defaults to f16, not Q4KM, and the effect of Q4KM is not very good, nor is it provided. All new versions of gemma-3-abliterated have been released; please re-download and test. Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of Qwen2.5-1.5B-Instruct created with abliteration (see this article to know more about it). Special thanks to @FailSpy for the original code and technique. Please follow him if you're interested in abliterated models. You can use huihuiai/qwen2.5-abliterate:1.5b directly, Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library:

This is an uncensored version of LLM360/K2-Think created with abliteration (see remove-refusals-with-transformers to know more about it). Transformers You can use `K2-Think` with Transformers. If you use `transformers.pipeline`, it will apply the chat template automatically. If you use `model.generate` directly, you need to apply the chat template mannually. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin: - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

This is an uncensored version of Qwen/Qwen2.5-VL-32B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. You can use huihuiai/qwen2.5-vl-abliterated:32b directly, Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

huihui-ai/DeepSeek-R1 This model converted from DeepSeek-R1 to BF16. Here we simply provide the conversion command and related information about ollama. If needed, we can upload the bf16 version. FP8 to BF16 1. Download deepseek-ai/DeepSeek-R1 model, requires approximately 641GB of space. 3. Convert to BF16, requires an additional approximately 1.3 TB of space. Here, you need to download the transformation code from the "inference" folder of deepseek-ai/DeepSeek-V3 BF16 to f16.gguf 1. Use the llama.cpp conversion program to convert DeepSeek-R1-bf16 to gguf format, requires an additional approximately 1.3 TB of space. 2. Use the llama.cpp quantitative program to quantitative model (llama-quantize needs to be compiled.), other quant option. Convert first Q2K, requires an additional approximately 227 GB of space. Use with ollama Note: this model requires Ollama 0.5.5

huihui-ai/Huihui-Qwen3-30B-A3B-Thinking-2507-abliterated This is an uncensored version of Qwen/Qwen3-30B-A3B-Thinking-2507 created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. Ablation was performed using a new and faster method, which yields better results. You can use huihuiai/qwen3-abliterated:30b-a3b-thinking-2507-q4KM directly, Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin（BTC):

huihui-ai/Huihui-Mistral-Small-3.2-24B-Instruct-2506-abliterated-v2 This is an uncensored version of mistralai/Mistral-Small-3.2-24B-Instruct-2506 created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. This version is based on user requirements, utilizing a specific ablation dataset to test whether the ablation goal can be achieved, which is different from the previous version huihui-ai/Huihui-Mistral-Small-3.2-24B-Instruct-2506-abliterated. It was only the text part that was processed, not the image part. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin: - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

This is an uncensored version of LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. You can use huihuiai/exaone3.5-abliterated directly,

This is an uncensored version of microsoft/Phi-4-multimodal-instruct created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. It was only the text part that was processed, not the image part. The abliterated model will no longer say "I'm sorry, but I cannot provide details or descriptions of images" Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of NousResearch/Hermes-3-Llama-3.2-3B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. You can use huihuiai/Hermes-3-Llama-3.2-abliterated directly,

This is an uncensored version of tencent/Hunyuan-MT-Chimera-7B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. If it's only for translation, use the original model without ablation. If it involves translation and other conversations, the ablated model can be used. You can use huihuiai/hunyuan-mt-abliterated:7b-chimera directly, Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin（BTC): - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

This is an uncensored version of janhq/Jan-v1-4B, achieved through fine-tuning with the TRL framework. The dataset used for fine-tuning is only in English, does not involve other languages, and all tests are conducted solely for English. - TRL: 0.21.0 - Transformers: 4.56.0.dev0 - Pytorch: 2.8.0+cu128 - Datasets: 3.6.0 - Tokenizers: 0.21.2 - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin（BTC):

huihui-ai/Huihui-Tongyi-DeepResearch-30B-A3B-abliterated This is an uncensored version of Alibaba-NLP/Tongyi-DeepResearch-30B-A3B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. Ablation was performed using a new and faster method, which yields better results. Note: During testing of the ablated model, we discovered that conversations sometimes exhibit text repetition issues. By testing the original model, we identified the root cause: in chat scenarios, the original model may produce garbled text or repetitions. This isn't necessarily caused by ablation. We've also made modifications, skipping ablation on layer 1, which might help reduce repetition or garbled output. As a result, we've re-uploaded the model-00001-of-00013.safetensors file. If you've already downloaded it, please re-download the file. You can use huihuiai/tongyi-deepresearch-abliterated directly, Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin（BTC): - Support our work on Ko-fi (https://ko-fi.com/huihuiai)!

huihui-ai/Huihui-Qwen3-Omni-30B-A3B-Captioner-abliterated This is an uncensored version of Qwen/Qwen3-Omni-30B-A3B-Captioner created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of PowerInfer/SmallThinker-3B-Preview created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. You can use huihuiai/smallthinker-abliterated directly ``` ollama run huihuiai/smallthinker-abliterated

This is an uncensored version of Qwen/Qwen2.5-7B-Instruct-1M created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. You can use huihuiai/qwen2.5-1m-abliterated directly

huihui-ai/Huihui-InternVL35-8B-Instruct-abliterated This is an uncensored version of OpenGVLab/InternVL35-8B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. The abliterated model will no longer say "I cannot assist with this request." - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

Model Overview Huihui-MoE-23B-A4B is a Mixture of Experts (MoE) language model developed by huihui.ai, built upon the Qwen/Qwen3-4B base model. It enhances the standard Transformer architecture by replacing MLP layers with MoE layers, each containing 8 experts, to achieve high performance with efficient inference. The model is designed for natural language processing tasks, including text generation, question answering, and conversational applications. The corresponding ablation version is huihui-ai/Huihui-MoE-23B-A4B-abliterated Note: The activated expert can handle numbers from 1 to 8, and can complete normal conversations as well. You can change the activation parameters using `/numexpertspertok `. After modifying the parameters, the model will be reloaded. - Architecture: Qwen3MoeForCausalLM model with 8 experts per layer (numexperts=8), activating 1-8 expert per token (numexpertspertok=1-8). - Total Parameters: ~23 billion (23B) - Activated Parameters: ~4 billion (4B) during inference, comparable to Qwen3-4B - Developer: huihui.ai - Release Date: June 2025 - License: Inherits the license of the Qwen3 base model (apache-2.0) `Qwen/Qwen3-4B` model was directly used for this expert, no fine-tune was applied. - Base Model: Qwen3-4B, pre-trained by the Qwen team. - Conversion: The model copies embeddings, self-attention, and normalization weights from Qwen3-4B, replacing MLP layers with MoE layers (8 experts). Gating weights are randomly initialized. - Fine-Tuning: Not fine-tuned; users are recommended to fine-tune for specific tasks to optimize expert routing. ollama You can use huihuiai/huihui-moe:23b directly, Switch the thinking toggle using /set think and /set nothink - Text Generation: Articles, dialogues, and creative writing. - Question Answering: Information retrieval and query resolution. - Conversational AI: Multi-turn dialogues for chatbots. - Research: Exploration of MoE architectures and efficient model scaling. - Fine-Tuning Required: Randomly initialized gating weights may lead to suboptimal expert utilization without fine-tuning. - Compatibility: Developed with transformers 4.52.4; ensure matching versions to avoid loading issues. - Inference Speed: While efficient for an MoE model, performance depends on hardware (GPU recommended). - Bias: Inherits potential biases from the Qwen3-4B base model; users should evaluate outputs for fairness. - Usage: Intended for research and responsible applications; avoid generating harmful or misleading content. - Developer: huihui.ai - Repository: huihui-ai/Huihui-MoE-23B-A4B (available locally or on Hugging Face) - Issues: Report bugs or request features via the repository or please send an email to [email protected] - Built upon the Qwen3-4B model by the Qwen team. - Built upon the Experts model by the Suayptalha team. - Powered by the Hugging Face transformers library.

MicroThinker-3B-Preview-v2, a new model fine-tuned from the huihui-ai/MicroThinker-3B-Preview model, focused on advancing AI reasoning capabilities. This model is superior to the huihui-ai/MicroThinker-3B-Preview model. This is just a test, but the performance is quite good. The fine-tuning process used 142k from the FineQwQ-142k dataset, maxlength(tokens) 21710, quantbits 4. The SFT (Supervised Fine-Tuning) process is divided into several steps, and no code needs to be written. 1. Create the environment. 3. Used only the huihui-ai/FineQwQ-142k, Trained for 1 epoch: 4. Save the final fine-tuned model. After you're done, input `exit` to exit. Replace the directories below with specific ones. This should create a new model directory: `checkpoint-8786-merged`, Rename the directory to `MicroThinker-3B-Preview-v2`, Copy or move this directory to the `huihui` directory. 5. Perform inference on the final fine-tuned model.

This is an uncensored version of ibm-granite/granite-3.2-2b-instruct created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. You can use huihuiai/granite3.2-abliterated directly If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of OpenGVLab/InternVL3-14B created with abliteration (see remove-refusals-with-transformers to know more about it). It was only the text part that was processed, not the image part. The abliterated model will no longer say "I cannot assist with this request." - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of Qwen/Qwen2.5-Coder-3B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). Qwen2.5-Coder uncensored version has covered six mainstream model sizes, 0.5, 1.5, 3, 7, 14, 32 billion parameters. If the desired result is not achieved, you can clear the conversation and try again. You can use huihuiai/qwen2.5-coder-abliterate:3b directly, Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library:

This is an uncensored version of THUDM/GLM-4.1V-9B-Thinking created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. It was only the text part that was processed, not the image part. Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin（BTC):

This is an uncensored version of ibm-granite/granite-vision-3.2-2b created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. It was only the text part that was processed, not the image part. You can use huihuiai/granite3.2-vision-abliterated directly Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library: If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is an uncensored version of Qwen2-VL-72B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. It was only the text part that was processed, not the image part. Usage You can use this model in your applications by loading it with Hugging Face's `transformers` library:

huihui-ai/Huihui-Mistral-Small-3.2-24B-Instruct-2506-abliterated This is an uncensored version of mistralai/Mistral-Small-3.2-24B-Instruct-2506 created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. It was only the text part that was processed, not the image part. - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. If you like it, please click 'like' and follow us for more updates. You can follow x.com/supporthuihui to get the latest model information from huihui.ai. Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This is a Uncensored Text-to-Video generation model, with 1.3 billion parameters, specifically fine-tuned for generating Not Safe For Work (NSFW) content. This model only modifies the key of model NSFW-API/NSFWWan1.3b and can be used under the original code Wan-Video/Wan2.1, The code can refer to savecheckpoint-all.py. NSFW Wan 1.3b T2V is a powerful text-to-video generation model, with 1.3 billion parameters, specifically fine-tuned for generating Not Safe For Work (NSFW) content. This model has been trained on an extensive and diverse dataset curated from the top 1,000 posts across approximately 1,250 NSFW-focused subreddits. The primary goal of Wan 2.1 is to provide a research and creative tool capable of generating coherent and thematically relevant short video clips based on text prompts within the adult content domain. It aims to understand and render a wide array of NSFW scenarios, aesthetics, and actions described in natural language. Architecture: Wan 2.1 (Text-to-Video Transformer Architecture) Parameters: 1.3 Billion Type: Text-to-Video (T2V) Specialization: NSFW Content Generation Note Since the checkpoint was only fine-tuned on images, you may see some deterioration throughout the video. That is to be expected, and in my testing was easily resolved by applying a LoRA, which I would recommend doing at this time to get the desired motion, style, and video quality. The model was trained on a dataset comprising the top 1,000 posts from approximately 1,250 distinct NSFW subreddits. This dataset was carefully curated to capture a broad spectrum of adult themes, visual styles, character archetypes, specific kinks, and actions prevalent in these online communities. The captions associated with the training data leveraged the language and tagging conventions found within these subreddits. For insights into effective prompting strategies for specific styles or content, please refer to the `prompting-guide.json` file included in this repository. Note: Due to the nature of the source material, the training dataset inherently contains explicit adult content. Hardware: Trained on a cluster of 8x A100 GPUs. Epochs: 10 epochs. Duration: Approximately 3 days. Checkpoints: Model weights are provided for each epoch (`wan1.3Be1.safetensors` through `wan1.3Be10.safetensors`). This allows users to select the checkpoint that best balances fidelity, generalization, and specific stylistic nuances for their needs. Early epochs might be more creative or varied, while later epochs may show higher fidelity to the training data. `wan1.3Be1.safetensors` `wan1.3Be2.safetensors` `wan1.3Be3.safetensors` `wan1.3Be4.safetensors` `wan1.3Be5.safetensors` `wan1.3Be6.safetensors` `wan1.3Be7.safetensors` `wan1.3Be8.safetensors` `wan1.3Be9.safetensors` `wan1.3Be10.safetensors` `prompting-guide.json`: This crucial JSON file contains an analysis of common keywords, phrases, and descriptive language associated with the content from various source subreddits. It is designed to help users craft more effective prompts by understanding the vocabulary the model was trained on for different niches. This model is intended for generating short video clips (typically a few seconds) from descriptive text prompts. 1. Select an Epoch Checkpoint: Experiment with different `wan1.3Be{i}.safetensors` files. Later epochs might offer more refined results for common themes, while earlier ones could be explored for broader interpretations. 2. Craft Your Prompt: Utilize natural language to describe the desired scene, subjects, actions, and style. 3. Consult `prompting-guide.json`: For best results, especially when targeting specific sub-community styles or niche fetishes, refer to the `prompting-guide.json`. This guide will provide insights into the terminology and phrasing most likely to elicit the desired output based on the training data's captioning patterns. 4. Generate: Use your preferred inference pipeline compatible with this model architecture. While Wan 2.1 1.3B T2V is a capable NSFW model on its own, its true strength for many users lies in its efficacy as a foundational base for training specialized LoRAs (Low-Rank Adaptations). The extensive NSFW training provides a robust understanding of: Core NSFW Anatomy: It already has a strong grasp of how to depict features like a penis, vagina, breasts, etc. Common Sexual Acts: Concepts like blowjobs, masturbation, various sexual positions, and basic interactions are part of its foundational knowledge. General NSFW Aesthetics: It understands common lighting, settings, and visual cues within adult content. This means you don't need to teach your LoRA these fundamental NSFW building blocks from scratch. Instead, you can focus your LoRA training dataset exclusively on the specific niche concept, character, artistic style, unique action, specific motion, or specialized terminology you want to master. NSFW Wan will effectively "fill in the rest," leveraging its broad NSFW foundation to complement your targeted LoRA training. This can lead to more efficient LoRA training and better results for highly specific NSFW content generation. Connect with other users, share your creations, get help with prompting, discuss model updates, and contribute to the community: We encourage active participation and feedback to help improve future iterations and resources! NSFW Focus: The model's knowledge is heavily biased towards the content prevalent in the NSFW subreddits it was trained on. It will likely perform poorly on SFW (Safe For Work) prompts or concepts far removed from its training data. Specificity & Artifacts: While trained for detail, the model may still produce visual artifacts, anatomical inaccuracies, or fail to perfectly capture highly complex or nuanced prompts. Video generation is an evolving field. Bias: The training data reflects the content, biases, preferences, and potentially problematic depictions present in the source NSFW communities. The model may generate content that perpetuates these biases. Safety: This model does not have built-in safety filters to prevent the generation of potentially harmful or offensive interpretations of NSFW content, beyond the scope of its training data. Users are responsible for the ethical application of the model. Temporal Coherence: While a T2V model, very long or complex actions might still exhibit some temporal inconsistencies. This model is intended for adult users (18+/21+ depending on local regulations) only. Consent and Harm: This model generates fictional, synthetic media. It must not be used to create non-consensual depictions of real individuals, to impersonate, defame, harass, or generate content that could cause harm. Legal Use: Users are solely responsible for ensuring that their use of this model and the content they generate complies with all applicable local, national, and international laws and regulations. Distribution: Exercise extreme caution and responsibility if distributing content generated by this model. Be mindful of platform terms of service and legal restrictions regarding adult content. No Endorsement: The creators of this model do not endorse or condone the creation or distribution of illegal, unethical, or harmful content. We strongly recommend users familiarize themselves with responsible AI practices and the potential societal impacts of generative NSFW media. The outputs of this model are entirely synthetic and computer-generated. They do not depict real people or events unless explicitly prompted to do so with user-provided data (which is not the intended use of this pre-trained model). The developers of this model are not responsible for the outputs created by users.

huihui-ai/Huihui-Kimi-Linear-48B-A3B-Instruct-abliterated This is an uncensored version of moonshotai/Kimi-Linear-48B-A3B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it). - Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs. - Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security. - Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences. - Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications. - Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content. - No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use. Donation Your donation helps us continue our further development and improvement, a cup of coffee can do it. - bitcoin:

This version only allows local loading of rednote-hilab/dots.llm1.inst using transformers, with only the local import issue modified and no other changes. Usage Copy the four files to the model directory, and then you can use the following program.

huihui-ai/grok-2 This Python script is designed to process and merge sharded weight files (in safetensors format) for a machine learning model, specifically targeting the xai-org/grok-2 model. The main functionalities include: Just a simple merge, without any inference code, and does not indicate whether the final model is reasonable or correct. 1. Collecting safetensors files: Locates all `pytorchmodel-.safetensors` files in the specified model directory. 2. Loading files into cache: Loads all safetensors files into memory and builds a key-to-file mapping. 3. Merging Tensor Parallel (TP) shards: Merges shards for tensor parallelism (TP=8) along specific dimensions and verifies the merged tensor shapes. 4. Grouping weights by layer: Organizes weights by model layer, with special weights (e.g., `lmhead.weight`, `model.embedtokens.weight`, and `model.norm.weight`) handled separately. 5. Saving merged weights: Saves the grouped weights as new safetensors files and generates a new index file pytorchmodel.bin.index.json. Features - Input: Safetensors files in the `xai-org/grok-2` model directory. - Output: Layer-organized safetensors files and an index file in the `huihui-ai/grok-2` directory. - Tensor Parallelism Support: Handles TP=8 shards, merging tensors along specific dimensions (`w1.weight` and `w3.weight` along dim=0, `w2.weight` along dim=1). - Error Handling: Includes warnings and handling for missing files, shape mismatches, and other exceptions. - Shape Validation: Verifies shapes for specific weights (e.g., MoE layer weights), ensuring merged tensors match expected shapes (e.g., `(16384, 8192)` or `(8192, 16384)`). 2. Place the script in an environment with the `xai-org/grok-2` model directory. 3. Run the script: 4. Output files will be saved in the `huihui-ai/grok-2` directory, including layer-organized safetensors files and an index file. Notes - Ensure the input directory `xai-org/grok-2` contains valid `pytorchmodel-.safetensors` files. - The script assumes a tensor parallelism degree of 8 (`tpcount = 8`). Modify the `tpcount` value in the script if needed. - Memory requirements may be high; run on a machine with sufficient memory. - If shards are missing or shapes mismatch, the script will print warnings and attempt to proceed.