Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use fredymad/roberta_estricto_2e-5_16_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fredymad/roberta_estricto_2e-5_16_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fredymad/roberta_estricto_2e-5_16_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fredymad/roberta_estricto_2e-5_16_2") model = AutoModelForSequenceClassification.from_pretrained("fredymad/roberta_estricto_2e-5_16_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 472f9b3144ac4a96f5a8eac6e5bf3d811c9e9ea6145e433f9d0e35e804b89187
- Size of remote file:
- 438 MB
- SHA256:
- 681c0b2e073c77a68fe1a763741c47d8c7fda3ff5bb6805e8450d7bdb3942fa1
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