Instructions to use moneco/llama3.2_100k_extra_train_bad_classes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moneco/llama3.2_100k_extra_train_bad_classes with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("moneco/llama3.2_100k_extra_train_bad_classes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from moneco/llama3.2_100k_extra_train_bad_classes: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/moneco/llama3.2_100k_extra_train_bad_classes/resolve/main/tokenizer.json
- Command line
-
hf download hf://moneco/llama3.2_100k_extra_train_bad_classes/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/moneco/llama3.2_100k_extra_train_bad_classes/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 988c127a7b0c8c6ded497ba4063bc2d82b73654da2f330673685f067403d94f0
- Size of remote file:
- 17.2 MB
- SHA256:
- 97259a2ef98adbd9197e93d7931212a327b6b0a496e1308e287d8766d90866ff
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