Instructions to use Angelakeke/RaTE-NER-Deberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Angelakeke/RaTE-NER-Deberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Angelakeke/RaTE-NER-Deberta")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Angelakeke/RaTE-NER-Deberta") model = AutoModelForTokenClassification.from_pretrained("Angelakeke/RaTE-NER-Deberta", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): b7ddd95
commit files to HF hub
Browse files- config.json +23 -23
- model.safetensors +2 -2
config.json
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{
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"_name_or_path": "
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"architectures": [
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"DebertaV2ForTokenClassification"
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],
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"layer_norm_eps": 1e-07,
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"max_position_embeddings": 512,
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{
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"_name_or_path": "deberta-v3-base",
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"architectures": [
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"DebertaV2ForTokenClassification"
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],
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"layer_norm_eps": 1e-07,
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"max_position_embeddings": 512,
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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size 735384420
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