Text Classification
Transformers
PyTorch
TensorBoard
Spanish
roberta
Generated from Trainer
acoso
twitter
cyberbullying
text-embeddings-inference
Instructions to use somosnlp-hackathon-2022/Detect-Acoso-Twitter-Es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use somosnlp-hackathon-2022/Detect-Acoso-Twitter-Es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="somosnlp-hackathon-2022/Detect-Acoso-Twitter-Es")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("somosnlp-hackathon-2022/Detect-Acoso-Twitter-Es") model = AutoModelForSequenceClassification.from_pretrained("somosnlp-hackathon-2022/Detect-Acoso-Twitter-Es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from somosnlp-hackathon-2022/Detect-Acoso-Twitter-Es: direct link, hf CLI and curl.
- Browser
- Download file 329 MB
-
https://huggingface.co/somosnlp-hackathon-2022/Detect-Acoso-Twitter-Es/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://somosnlp-hackathon-2022/Detect-Acoso-Twitter-Es/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/somosnlp-hackathon-2022/Detect-Acoso-Twitter-Es/resolve/main/pytorch_model.bin
329 MB
- Xet hash:
- fb2fae6d12cdf0e423729ad9c5d779b4735d6170fe007e61fc0b0a489630920f
- Size of remote file:
- 329 MB
- SHA256:
- 5e16ecaf91067326878bf1476967e6eddcdf08d0a5d89136a6dff64f7c11d696
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