Instructions to use dusersad12/BestLLM-EvalRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/BestLLM-EvalRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dusersad12/BestLLM-EvalRepo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dusersad12/BestLLM-EvalRepo") model = AutoModel.from_pretrained("dusersad12/BestLLM-EvalRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dusersad12/BestLLM-EvalRepo: direct link, hf CLI and curl.
- Browser
- Download file 28 Bytes
-
https://huggingface.co/dusersad12/BestLLM-EvalRepo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dusersad12/BestLLM-EvalRepo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dusersad12/BestLLM-EvalRepo/resolve/main/pytorch_model.bin
28 Bytes
- Xet hash:
- 15d2c4a6d415372ab351860956dbfbce1b45cf5c70b2f740b1ad789c20f2d517
- Size of remote file:
- 28 Bytes
- SHA256:
- 90bb09a8f02636abccc8eb73338f40ed45c4c3887005445aea76200a96f049cd
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