Instructions to use toolathlonEval/SparseTieModel-TestRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toolathlonEval/SparseTieModel-TestRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="toolathlonEval/SparseTieModel-TestRepo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("toolathlonEval/SparseTieModel-TestRepo") model = AutoModel.from_pretrained("toolathlonEval/SparseTieModel-TestRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload selected checkpoint (step_500) with highest eval_accuracy 0.702
Browse files- config.json +5 -0
- pytorch_model.bin +3 -0
config.json
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{
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"model_type": "bert",
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"architectures": ["BertModel"],
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"training_note": ""
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:fdbadbba4530f71cbe18e291a4f89631b9ce4446bca00f9c4432fb628299da51
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size 35
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