Text Classification
Transformers
Safetensors
English
distilbert
book-genre-classification
mlops
Eval Results (legacy)
text-embeddings-inference
Instructions to use sureshbabugandla/ML_OPS_ASSIGNMENT2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sureshbabugandla/ML_OPS_ASSIGNMENT2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sureshbabugandla/ML_OPS_ASSIGNMENT2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sureshbabugandla/ML_OPS_ASSIGNMENT2") model = AutoModelForSequenceClassification.from_pretrained("sureshbabugandla/ML_OPS_ASSIGNMENT2") - Notebooks
- Google Colab
- Kaggle
Upload DistilBertForSequenceClassification
Browse files- config.json +3 -1
- model.safetensors +1 -1
config.json
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"n_layers": 6,
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"output_past": true,
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"pad_token_id": 0,
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"tie_word_embeddings": true,
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"transformers_version": "5.
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"vocab_size": 28996
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}
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"n_layers": 6,
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"output_past": true,
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"pad_token_id": 0,
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"problem_type": "single_label_classification",
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"tie_word_embeddings": true,
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"transformers_version": "5.0.0",
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"use_cache": false,
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"vocab_size": 28996
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 263163144
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