Instructions to use dhtocks/Named-Entity-Recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dhtocks/Named-Entity-Recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dhtocks/Named-Entity-Recognition", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dhtocks/Named-Entity-Recognition") model = AutoModelForTokenClassification.from_pretrained("dhtocks/Named-Entity-Recognition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add model
Browse files- config.json +2 -6
- pytorch_model.bin +2 -2
config.json
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"3": "LABEL_3",
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"4": "LABEL_4",
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"5": "LABEL_5",
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"6": "LABEL_6"
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"8": "LABEL_8"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"LABEL_3": 3,
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"LABEL_4": 4,
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"LABEL_8": 8
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"3": "LABEL_3",
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"4": "LABEL_4",
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"5": "LABEL_5",
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"6": "LABEL_6"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"LABEL_3": 3,
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"LABEL_4": 4,
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"LABEL_5": 5,
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"LABEL_6": 6
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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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
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version https://git-lfs.github.com/spec/v1
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oid sha256:cb4e428fa867576985563df92f79fdf2fbdac3de6ef3b6f216b70d4cdb242eb6
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size 496323633
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