Instructions to use nadellaroshni/test_model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nadellaroshni/test_model2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nadellaroshni/test_model2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nadellaroshni/test_model2") model = AutoModelForSequenceClassification.from_pretrained("nadellaroshni/test_model2") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- model.safetensors +1 -1
- tokenizer.json +2 -2
- tokenizer_config.json +0 -2
- training_args.bin +1 -1
model.safetensors
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oid sha256:25df5f6bcbf4a706ae49282bc99683a5e246628fdc80da64d73031d47cfedbb6
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tokenizer.json
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tokenizer_config.json
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},
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_basic_tokenize": true,
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"never_split": null,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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},
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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"do_lower_case": true,
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"mask_token": "[MASK]",
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"model_max_length": 512,
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"strip_accents": null,
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training_args.bin
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oid sha256:6f3973722fece9334c17c2dd4b5240e0d0a11a2d942e44af54469dc4b47fb231
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size 4664
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