Instructions to use SuchithTissera/text_analytics_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SuchithTissera/text_analytics_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SuchithTissera/text_analytics_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SuchithTissera/text_analytics_model") model = AutoModelForSequenceClassification.from_pretrained("SuchithTissera/text_analytics_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload DistilBertForSequenceClassification
Browse files- config.json +10 -10
- model.safetensors +1 -1
config.json
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"eos_token_id": null,
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"hidden_dim": 3072,
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"id2label": {
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"initializer_range": 0.02,
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"label2id": {
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"eos_token_id": null,
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"hidden_dim": 3072,
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"id2label": {
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"0": "Business",
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"1": "Opinion",
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"2": "Political Gossip",
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"3": "Sports",
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"4": "World news"
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},
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"initializer_range": 0.02,
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"label2id": {
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"Business": 0,
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"Opinion": 1,
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"Political Gossip": 2,
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"Sports": 3,
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"World news": 4
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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model.safetensors
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size 267841796
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version https://git-lfs.github.com/spec/v1
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size 267841796
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