Theta-Lev
YandexGPT-5-Lite-8B-instruct-Q5_K_M-GGUF
YandexGPT 5 Lite 8B Instruct Q8 GGUF
Theta-Lev/YandexGPT-5-Lite-8B-instruct-Q80-GGUF This model was converted to GGUF format from `yandex/YandexGPT-5-Lite-8B-instruct` 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).
DeepSeek-V2-Lite-Q8_0-GGUF
deepseek-coder-6.7b-instruct-Q8_0-GGUF
L3.1-Dark-Reasoning-LewdPlay-evo-Hermes-R1-Uncensored-8B-Q5_K_M-GGUF
L3-SnowStorm-v1.15-4x8B-B-Q8_0-GGUF
L3-SnowStorm-v1.15-4x8B-B-Q5_K_M-GGUF
internlm2-math-plus-7b-Q8_0-GGUF
rho-math-1b-interpreter-v0.1-Q8_0-GGUF
RedPajama-INCITE-Instruct-3B-v1-Q8_0-GGUF
deepseek-math-7b-instruct-Q8_0-GGUF
Llama-3.1-Minitron-4B-Width-Base-Q8_0-GGUF
deepseek-math-7b-rl-Q8_0-GGUF
rho-math-7b-interpreter-v0.1-Q8_0-GGUF
Llama-3.1-Minitron-4B-Depth-Base-Q8_0-GGUF
Mistral-Nemo-Instruct-2407-Q8_0-GGUF
Qwen2.5-VL-3B-Instruct-Q8_0-GGUF
Qwen2.5-MOE-6x1.5B-DeepSeek-Reasoning-e32-Q8_0-GGUF
Theta-Lev/Qwen2.5-MOE-6x1.5B-DeepSeek-Reasoning-e32-Q80-GGUF This model was converted to GGUF format from `DavidAU/Qwen2.5-MOE-6x1.5B-DeepSeek-Reasoning-e32` 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).
Qwen2.5-VL-7B-Instruct-Q8_0-GGUF
Theta-Lev/Qwen2.5-VL-7B-Instruct-Q80-GGUF This model was converted to GGUF format from `Qwen/Qwen2.5-VL-7B-Instruct` 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).