Instructions to use mfatikk/llumi70b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mfatikk/llumi70b with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mfatikk/llumi70b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from mfatikk/llumi70b: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/mfatikk/llumi70b/resolve/main/tokenizer.json
- Command line
-
hf download hf://mfatikk/llumi70b/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/mfatikk/llumi70b/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- b9b7699d060f9eac415430f7b93e1b881f261e0137653463724ce3cf55fa2ad0
- Size of remote file:
- 17.2 MB
- SHA256:
- 28f68c30a4056f2e5d53416b382e328409a81cfd495e74b7f8a5a14722c5df71
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