ysn-rfd

TestFIBOIDENFFN Model creator: ysn-rfd Original model: ysn-rfd/TestFIBOIDENFFN GGUF quantization: provided by ysn-rfd using `llama.cpp` Special thanks 🙏 Special thanks to Georgi Gerganov and the whole team working on llama.cpp for making all of this possible. Use with Ollama

FIBOIDENMODEL Model creator: ysn-rfd Original model: ysn-rfd/FIBOIDENMODEL GGUF quantization: provided by ysn-rfd using `llama.cpp` Special thanks 🙏 Special thanks to Georgi Gerganov and the whole team working on llama.cpp for making all of this possible. Use with Ollama

Example usage: - For text only LLMs: llama-cli --hf repoid/modelname -p "why is the sky blue?" - For multimodal models: llama-mtmd-cli -m modelname.gguf --mmproj mmprojfile.gguf Ollama An Ollama Modelfile is included for easy deployment.

ysn-rfd/WizardLM-7B-Uncensored-GGUF This model was converted to GGUF format from `cognitivecomputations/WizardLM-7B-Uncensored` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMACURL=1` flag along with other hardware-specific flags (for ex: LLAMACUDA=1 for Nvidia GPUs on Linux).

ysn-rfd/qwen31.7bpersian-Q80-GGUF This model was converted to GGUF format from `ysn-rfd/qwen31.7bpersian` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMACURL=1` flag along with other hardware-specific flags (for ex: LLAMACUDA=1 for Nvidia GPUs on Linux).

text2image-prompt-generator Model creator: succinctly Original model: succinctly/text2image-prompt-generator GGUF quantization: provided by ysn-rfd using `llama.cpp` Special thanks 🙏 Special thanks to Georgi Gerganov and the whole team working on llama.cpp for making all of this possible. Use with Ollama

- Developed by: ysn-rfd - License: apache-2.0 - Finetuned from model : unsloth/Qwen3-1.7B-unsloth-bnb-4bit This qwen3 model was trained 2x faster with Unsloth and Huggingface's TRL library.

ysn-rfd/Huihui-MoE-12B-A4B-abliterated-Q4KM-GGUF This model was converted to GGUF format from `huihui-ai/Huihui-MoE-12B-A4B-abliterated` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMACURL=1` flag along with other hardware-specific flags (for ex: LLAMACUDA=1 for Nvidia GPUs on Linux).

ysn-rfd/DeepSeek-R1-Distill-Qwen-7B-GGUF This model was converted to GGUF format from `deepseek-ai/DeepSeek-R1-Distill-Qwen-7B` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMACURL=1` flag along with other hardware-specific flags (for ex: LLAMACUDA=1 for Nvidia GPUs on Linux).

- Developed by: ysn-rfd - License: apache-2.0 - Finetuned from model : unsloth/Qwen3-1.7B-unsloth-bnb-4bit

- Developed by: ysn-rfd - License: apache-2.0 - Finetuned from model : unsloth/Qwen3-1.7B-unsloth-bnb-4bit

ysn-rfd/gemma-3-4b-it-qat-int4-unquantized-Q4KM-GGUF This model was converted to GGUF format from `google/gemma-3-4b-it-qat-int4-unquantized` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMACURL=1` flag along with other hardware-specific flags (for ex: LLAMACUDA=1 for Nvidia GPUs on Linux).

- Developed by: ysn-rfd - License: apache-2.0 - Finetuned from model : unsloth/Qwen3-1.7B-unsloth-bnb-4bit This qwen3 model was trained 2x faster with Unsloth and Huggingface's TRL library.

- Developed by: ysnrfd - License: apache-2.0 - Finetuned from model : unsloth/gemma-3n-e4b-it-unsloth-bnb-4bit

ysn-rfd/DAN-Qwen3-1.7B-Q80-GGUF This model was converted to GGUF format from `UnfilteredAI/DAN-Qwen3-1.7B` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMACURL=1` flag along with other hardware-specific flags (for ex: LLAMACUDA=1 for Nvidia GPUs on Linux).

ysn-rfd/gemma-3-4b-it-qat-int4-unquantized-Q80-GGUF This model was converted to GGUF format from `google/gemma-3-4b-it-qat-int4-unquantized` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMACURL=1` flag along with other hardware-specific flags (for ex: LLAMACUDA=1 for Nvidia GPUs on Linux).

ysn-rfd/stable-code-instruct-3b-Q80-GGUF This model was converted to GGUF format from `stabilityai/stable-code-instruct-3b` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMACURL=1` flag along with other hardware-specific flags (for ex: LLAMACUDA=1 for Nvidia GPUs on Linux).

WARNINNGS: This Model IS Pre-Trained, in the future will be finetuned. The First Persian SLM By YSNRFD (YASIN ARYANFARD) and AMIRHOSSEIN MEHRDOOST, This Model support Only Persian text Inputs, In The Future I Want Add Englih Language Support. - Developed by: ysnrfd (yasin aryanfard) - Funded by: ysnrfd (yasin aryanfard) and Amirhossein Mehrdoost (https://huggingface.co/fibonacciai) - Shared by: ysnrfd (yasin aryanfard) and Amirhossein Mehrdoost (https://huggingface.co/fibonacciai) - Model type: SLM - Language(s) (NLP): Persian - License: ysnrfd LICENSE ysnrfd Sample Persian Text LINK: https://huggingface.co/datasets/ysn-rfd/fibonaccialpacatosharegptgptformatconvertnewdatasetrelease - Hardware Type: Nvidia Tesla T4 (1) - Hours used: 1H - Cloud Provider: Google Colab

ysn-rfd/Promt-generator-Q80-GGUF This model was converted to GGUF format from `UnfilteredAI/Promt-generator` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMACURL=1` flag along with other hardware-specific flags (for ex: LLAMACUDA=1 for Nvidia GPUs on Linux).

ysn-rfd/gpt2-large-Q2K-GGUF This model was converted to GGUF format from `openai-community/gpt2-large` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMACURL=1` flag along with other hardware-specific flags (for ex: LLAMACUDA=1 for Nvidia GPUs on Linux).

ysn-rfd/DeepScaleR-1.5B-Preview-Q80-GGUF This model was converted to GGUF format from `agentica-org/DeepScaleR-1.5B-Preview` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMACURL=1` flag along with other hardware-specific flags (for ex: LLAMACUDA=1 for Nvidia GPUs on Linux).

ysn-rfd/Open-RS3-Q80-GGUF This model was converted to GGUF format from `knoveleng/Open-RS3` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMACURL=1` flag along with other hardware-specific flags (for ex: LLAMACUDA=1 for Nvidia GPUs on Linux).

ysn-rfd/fibonaccitestrelease-Q4KM-GGUF This model was converted to GGUF format from `ysn-rfd/fibonaccitestrelease` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMACURL=1` flag along with other hardware-specific flags (for ex: LLAMACUDA=1 for Nvidia GPUs on Linux).

ysn-rfd/gpt2-medium-Q2K-GGUF This model was converted to GGUF format from `openai-community/gpt2-medium` using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well. Step 2: Move into the llama.cpp folder and build it with `LLAMACURL=1` flag along with other hardware-specific flags (for ex: LLAMACUDA=1 for Nvidia GPUs on Linux).

- Developed by: ysn-rfd - License: apache-2.0 - Finetuned from model : unsloth/gemma-3n-e4b-it-unsloth-bnb-4bit This gemma3n model was trained 2x faster with Unsloth and Huggingface's TRL library.

- Developed by: ysn-rfd - License: apache-2.0 - Finetuned from model : unsloth/mistral-7b-instruct-v0.3-bnb-4bit This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.

- Developed by: ysn-rfd - License: apache-2.0 - Finetuned from model : unsloth/Qwen3-1.7B-unsloth-bnb-4bit This qwen3 model was trained 2x faster with Unsloth and Huggingface's TRL library.

- Developed by: ysn-rfd - License: apache-2.0 - Finetuned from model : unsloth/Qwen3-1.7B-unsloth-bnb-4bit This qwen3 model was trained 2x faster with Unsloth and Huggingface's TRL library.