Instructions to use dusersad12/SentinelLM-EvalRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/SentinelLM-EvalRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dusersad12/SentinelLM-EvalRepo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dusersad12/SentinelLM-EvalRepo") model = AutoModel.from_pretrained("dusersad12/SentinelLM-EvalRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload best checkpoint step_800 (highest eval_accuracy 0.730): pytorch_model.bin
Browse files- pytorch_model.bin +3 -0
pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:34bd7b58f12ab6a297adc6d225cfcb20bbea4838c89ec0cf2a38ed769fe6c113
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size 172
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