Text Classification
Transformers
PyTorch
Safetensors
xlm-roberta
TextClassificationPipeline
text-embeddings-inference
Instructions to use ssharoff/genres with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ssharoff/genres with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ssharoff/genres")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ssharoff/genres") model = AutoModelForSequenceClassification.from_pretrained("ssharoff/genres") - Notebooks
- Google Colab
- Kaggle
File size: 499 Bytes
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"bos_token": "<s>",
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"__type": "AddedToken",
"content": "<mask>",
"lstrip": true,
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"rstrip": false,
"single_word": false
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"model_max_length": 512,
"name_or_path": "xlm-roberta-base",
"pad_token": "<pad>",
"problem_type": "multi_label_classification",
"sep_token": "</s>",
"special_tokens_map_file": null,
"tokenizer_class": "XLMRobertaTokenizer",
"unk_token": "<unk>"
}
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