Instructions to use hf-internal-testing/tiny-random-T5ForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-T5ForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-T5ForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-T5ForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-T5ForTokenClassification") - Notebooks
- Google Colab
- Kaggle
Update tiny models for T5ForTokenClassification
Browse files- config.json +1 -1
- model.safetensors +1 -1
- tokenizer.json +0 -0
config.json
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"relative_attention_max_distance": 128,
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"relative_attention_num_buckets": 8,
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"torch_dtype": "float32",
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"transformers_version": "4.
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"use_cache": true,
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"vocab_size": 1302
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}
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"relative_attention_max_distance": 128,
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"relative_attention_num_buckets": 8,
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"torch_dtype": "float32",
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"transformers_version": "4.39.0.dev0",
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"use_cache": true,
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"vocab_size": 1302
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 221848
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version https://git-lfs.github.com/spec/v1
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oid sha256:cd145d068356b23fa2a760958efb1d06453dabad93d7bdbec54b1169c48b43b8
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size 221848
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tokenizer.json
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