Instructions to use mlc-ai/NeuralHermes-2.5-Mistral-7B-q4f16_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-q4f16_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_105.bin from mlc-ai/NeuralHermes-2.5-Mistral-7B-q4f16_1-MLC: direct link, hf CLI and curl.
- Browser
- Download file 33 MB
-
https://huggingface.co/mlc-ai/NeuralHermes-2.5-Mistral-7B-q4f16_1-MLC/resolve/a10f84d2ecd33c05a4e4910bfa2fd64111c38ba0/params_shard_105.bin
- Command line
-
hf download hf://mlc-ai/NeuralHermes-2.5-Mistral-7B-q4f16_1-MLC@a10f84d2ecd33c05a4e4910bfa2fd64111c38ba0/params_shard_105.bin
-
curl -L -o params_shard_105.bin https://huggingface.co/mlc-ai/NeuralHermes-2.5-Mistral-7B-q4f16_1-MLC/resolve/a10f84d2ecd33c05a4e4910bfa2fd64111c38ba0/params_shard_105.bin
33 MB
- Xet hash:
- 226109df533d22bedf2c91a4bf5a89c02323199581fd4f4dfe102c49d0112bad
- Size of remote file:
- 33 MB
- SHA256:
- 2041f67b4b8ad01ca32a1f886d799b199bcf432c58853764ad00a3ca15f44083
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