Instructions to use hf-internal-testing/tiny-random-GPTNeoForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GPTNeoForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-GPTNeoForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPTNeoForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-GPTNeoForTokenClassification") - Notebooks
- Google Colab
- Kaggle
Commit ·
c35b462
1
Parent(s): d5208e7
Update tiny models for GPTNeoForTokenClassification
Browse files- config.json +1 -1
- pytorch_model.bin +1 -1
config.json
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"pad_token_id": 1023,
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"resid_dropout": 0.0,
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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": 1024,
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"window_size": 7
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"pad_token_id": 1023,
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"resid_dropout": 0.0,
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"torch_dtype": "float32",
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"transformers_version": "4.30.0.dev0",
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"use_cache": true,
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"vocab_size": 1024,
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"window_size": 7
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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:
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size 1467831
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version https://git-lfs.github.com/spec/v1
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oid sha256:1dbae0013a0c3c72d9631a7389c67aa07702f7f41f0d73c0475b6fd9117efcb5
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size 1467831
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