Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use raulgdp/Analisis-sentimientos-xml-roberta-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raulgdp/Analisis-sentimientos-xml-roberta-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="raulgdp/Analisis-sentimientos-xml-roberta-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("raulgdp/Analisis-sentimientos-xml-roberta-2") model = AutoModelForSequenceClassification.from_pretrained("raulgdp/Analisis-sentimientos-xml-roberta-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files
config.json
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.40.
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250002
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.40.0",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250002
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model.safetensors
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runs/Apr29_04-43-28_7c98c5c35121/events.out.tfevents.1714365905.7c98c5c35121.552.0
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training_args.bin
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size 4984
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