Instructions to use npark95/finetuned_ClinicalLongformer_CAT_020425 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use npark95/finetuned_ClinicalLongformer_CAT_020425 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="npark95/finetuned_ClinicalLongformer_CAT_020425")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("npark95/finetuned_ClinicalLongformer_CAT_020425") model = AutoModelForSequenceClassification.from_pretrained("npark95/finetuned_ClinicalLongformer_CAT_020425") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- config.json +4 -4
- model.safetensors +1 -1
- training_args.bin +1 -1
config.json
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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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"
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"
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},
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"ignore_attention_mask": false,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"Cat2":
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"Cat3":
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 4098,
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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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"0": "Cat2",
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"1": "Cat3"
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},
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"ignore_attention_mask": false,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"Cat2": 0,
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"Cat3": 1
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 4098,
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 594678184
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version https://git-lfs.github.com/spec/v1
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oid sha256:8bc2af7aa571532ac079334662f6ced5d9c3b356b41c9e35e668b4a2cca07e0e
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size 594678184
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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size 5368
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version https://git-lfs.github.com/spec/v1
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oid sha256:5ae7537ca2075de55eddc1d6e904bb31e1782faee259594f789fcb6eb06e9e80
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size 5368
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