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AI モデル 85003
- 20261016_rar-medicine_static_qwen3-4b_norm3200_impl-verl_s11_step-038↗
HYU-NLP-EVAL
- IceWhiskeyRP-7b-8bpw-exl2↗
icefog72
If you remove the `--local-dir-use-symlinks False` parameter, the files will instead be stored in the central Hugging Face cache directory (default location on Linux is: `~/.cache/huggingface`), and symlinks will be added to the specified `--local-dir`, pointing to their real location in the cache. This allows for interrupted downloads to be resumed, and allows you to quickly clone the repo to multiple places on disk without triggering a download again. The downside, and the reason why I don't list that as the default option, is that the files are then hidden away in a cache folder and it's harder to know where your disk space is being used, and to clear it up if/when you want to remove a download model. The cache location can be changed with the `HF_HOME` environment variable, and/or the `--cache-dir` parameter to `huggingface-cli`. For more documentation on downloading with `huggingface-cli`, please see: HF -> Hub Python Library -> Download files -> Download from the CLI.
- K2-Think-V2↗
IFM
- Hunyuan-MT-7B-Q4_K_M-GGUF↗
imikeliu
This model was converted to GGUF format from `tencent/Hunyuan-MT-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. 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 `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
- GLM-5.3-Flash-MLX-Q9↗
inferencerlabs
- Hy-MT2-30B-A3B-int4-AutoRound↗
Intel
- qwen3.6-35b-a3b-crown-halo-mtp-dynamic↗
jcbtc
- phi-4-DASHQ-Q2-GGUF↗
jkim96
- llama3.1-8b-16x4-emo-style-routed-lora-moe↗
Jongbin-kr
- Nemotron-3-Nano-Omni-AEON-Ultimate-Uncensored-BF16-Q3_K_M-GGUF↗
kainecorneko