Instructions to use dusersad12/MyBrilliantModel-EvalRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/MyBrilliantModel-EvalRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dusersad12/MyBrilliantModel-EvalRepo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dusersad12/MyBrilliantModel-EvalRepo") model = AutoModel.from_pretrained("dusersad12/MyBrilliantModel-EvalRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload MyBrilliantModel (best checkpoint step_1000) with full 17-benchmark evaluation results
ee63f9c verified Download pytorch_model.bin from dusersad12/MyBrilliantModel-EvalRepo: direct link, hf CLI and curl.
- Browser
- Download file 62 Bytes
-
https://huggingface.co/dusersad12/MyBrilliantModel-EvalRepo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dusersad12/MyBrilliantModel-EvalRepo/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/dusersad12/MyBrilliantModel-EvalRepo/resolve/main/pytorch_model.bin
62 Bytes
- Xet hash:
- 302696691815dbd9f6b78842862e8435857defe2a6dff20eb61e4c07c488c0cd
- Size of remote file:
- 62 Bytes
- SHA256:
- 9e41ea8bb84480a0169ae671f3c7c0c8d51861209d80c9396d0ae4d4f2525a83
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