Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use oskrmiguel/roberta-base-bne-clasificacion-de-texto-supervisado with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oskrmiguel/roberta-base-bne-clasificacion-de-texto-supervisado with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="oskrmiguel/roberta-base-bne-clasificacion-de-texto-supervisado")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("oskrmiguel/roberta-base-bne-clasificacion-de-texto-supervisado") model = AutoModelForSequenceClassification.from_pretrained("oskrmiguel/roberta-base-bne-clasificacion-de-texto-supervisado", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from oskrmiguel/roberta-base-bne-clasificacion-de-texto-supervisado: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/oskrmiguel/roberta-base-bne-clasificacion-de-texto-supervisado/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://oskrmiguel/roberta-base-bne-clasificacion-de-texto-supervisado/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/oskrmiguel/roberta-base-bne-clasificacion-de-texto-supervisado/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- bb679a4e5bdee0c42fc8c2a5d4b0df5b0a63bb6f036b7b1751e684440b722e76
- Size of remote file:
- 499 MB
- SHA256:
- 4659adc46f60635dcb2d410bcbdeb4c3085e91a63c2d2a7f05add613b9d046ca
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