Instructions to use go76dof/firstTestModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use go76dof/firstTestModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="go76dof/firstTestModel", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("go76dof/firstTestModel", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
feat: upload custom trained BPE tokenizer from scratch
Browse files- tokenizer_config.json +1 -1
tokenizer_config.json
CHANGED
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@@ -6,5 +6,5 @@
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"tokenizer_class": "TokenizersBackend",
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"
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}
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"pad_token": "[PAD]",
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"sep_token": "[SEP]",
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"tokenizer_class": "TokenizersBackend",
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"unk_token": "[UNK]"
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}
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