Instructions to use CouchCat/ma_sa_v7_distil with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CouchCat/ma_sa_v7_distil with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CouchCat/ma_sa_v7_distil")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CouchCat/ma_sa_v7_distil") model = AutoModelForSequenceClassification.from_pretrained("CouchCat/ma_sa_v7_distil") - Notebooks
- Google Colab
- Kaggle
update the config on id2label and label2id with more meaningful labels
Browse files- config.json +6 -6
config.json
CHANGED
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@@ -8,15 +8,15 @@
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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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},
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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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"max_position_embeddings": 512,
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"model_type": "distilbert",
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "negative",
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"1": "neutral",
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"2": "positive"
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},
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"initializer_range": 0.02,
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"label2id": {
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"negative": 0,
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"neutral": 1,
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"positive": 2
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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