Instructions to use epiphacc/csabstract-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use epiphacc/csabstract-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="epiphacc/csabstract-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("epiphacc/csabstract-classification") model = AutoModelForSequenceClassification.from_pretrained("epiphacc/csabstract-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add config
Browse files- config.json +12 -12
config.json
CHANGED
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@@ -1,5 +1,5 @@
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{
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"_name_or_path": "
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "
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"1": "
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"2": "
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"3": "
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"4": "
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},
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"initializer_range": 0.02,
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"label2id": {
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"
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"
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"
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"
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"
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.
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"vocab_size": 30522
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}
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{
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"_name_or_path": "epiphacc/csabstract-classification",
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "BACKGROUND",
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"1": "OBJECTIVE",
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"2": "METHODS",
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"3": "RESULTS",
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"4": "COCLUSIONS"
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},
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"initializer_range": 0.02,
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"label2id": {
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"BACKGROUND": 0,
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"COCLUSIONS": 4,
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"METHODS": 2,
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"OBJECTIVE": 1,
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"RESULTS": 3
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.21.1",
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"vocab_size": 30522
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}
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