Instructions to use mlc-ai/NeuralHermes-2.5-Mistral-7B-q3f16_1-MLC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLC-LLM
How to use mlc-ai/NeuralHermes-2.5-Mistral-7B-q3f16_1-MLC with MLC-LLM:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Download params_shard_46.bin from mlc-ai/NeuralHermes-2.5-Mistral-7B-q3f16_1-MLC: direct link, hf CLI and curl.
- Browser
- Download file 27.8 MB
-
https://huggingface.co/mlc-ai/NeuralHermes-2.5-Mistral-7B-q3f16_1-MLC/resolve/main/params_shard_46.bin
- Command line
-
hf download hf://mlc-ai/NeuralHermes-2.5-Mistral-7B-q3f16_1-MLC/params_shard_46.bin
-
curl -L -o params_shard_46.bin https://huggingface.co/mlc-ai/NeuralHermes-2.5-Mistral-7B-q3f16_1-MLC/resolve/main/params_shard_46.bin
27.8 MB
- Xet hash:
- 216a9a65be0d2cf8c200bd3273e4c59a29d6dbaf37622a2229cf8aeb8bbc93c9
- Size of remote file:
- 27.8 MB
- SHA256:
- 65e7adceb709e1d163c12b3b96956df32e0b4bf16d8fedb538ea61847feaa176
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