Text Classification
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
roberta
autogenerated-modelcard
text-embeddings-inference
Instructions to use FacebookAI/roberta-large-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FacebookAI/roberta-large-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FacebookAI/roberta-large-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FacebookAI/roberta-large-mnli") model = AutoModelForSequenceClassification.from_pretrained("FacebookAI/roberta-large-mnli") - Inference
- Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +6 -6
config.json
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"id2label": {
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"0": "
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"1": "
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"2": "
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"id2label": {
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"0": "CONTRADICTION",
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"1": "NEUTRAL",
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"2": "ENTAILMENT"
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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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"CONTRADICTION": 0,
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"NEUTRAL": 1,
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"ENTAILMENT": 2
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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