Instructions to use 2Allight4/LLM_A1_128_50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 2Allight4/LLM_A1_128_50 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("2Allight4/LLM_A1_128_50", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from 2Allight4/LLM_A1_128_50: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/2Allight4/LLM_A1_128_50/resolve/main/tokenizer.json
- Command line
-
hf download hf://2Allight4/LLM_A1_128_50/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/2Allight4/LLM_A1_128_50/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 7745f5a7892d08bd57f6a3cbfff31b32413a0900cf8b096ca3dab91cdc02dd61
- Size of remote file:
- 17.2 MB
- SHA256:
- 3e47604acf96905a0f797692762c3318b6aa9e99f8c5d9ffbcb5995f60af24ea
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