Text Classification
Transformers
TensorBoard
Safetensors
roberta
trl
reward-trainer
Generated from Trainer
text-embeddings-inference
Instructions to use paulovsantanas/reward_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paulovsantanas/reward_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="paulovsantanas/reward_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("paulovsantanas/reward_model") model = AutoModelForSequenceClassification.from_pretrained("paulovsantanas/reward_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 916c133eb7716394242707fecb2af889cc00d4b40c341ef9ff6546ae174afd37
- Size of remote file:
- 5.24 kB
- SHA256:
- 8f9f5956d7398dd70ec5eb04aa255f0c3a7452534be0e75bccb9e48f403c37e4
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