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_31.bin from mlc-ai/NeuralHermes-2.5-Mistral-7B-q4f16_1-MLC: direct link, hf CLI and curl.
- Browser
- Download file 22 MB
-
https://huggingface.co/mlc-ai/NeuralHermes-2.5-Mistral-7B-q4f16_1-MLC/resolve/a10f84d2ecd33c05a4e4910bfa2fd64111c38ba0/params_shard_31.bin
- Command line
-
hf download hf://mlc-ai/NeuralHermes-2.5-Mistral-7B-q4f16_1-MLC@a10f84d2ecd33c05a4e4910bfa2fd64111c38ba0/params_shard_31.bin
-
curl -L -o params_shard_31.bin https://huggingface.co/mlc-ai/NeuralHermes-2.5-Mistral-7B-q4f16_1-MLC/resolve/a10f84d2ecd33c05a4e4910bfa2fd64111c38ba0/params_shard_31.bin
22 MB
- Xet hash:
- c848c4e4fe33d96c20c9669187d188642d13bf8df5eeb26418467cb38badbf28
- Size of remote file:
- 22 MB
- SHA256:
- adf28074d3e9b79216e887fa03092d06e13c376b255e952acb15cd0ebae40667
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