Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Keithsu/sawyer-reward with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Keithsu/sawyer-reward with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Keithsu/sawyer-reward")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Keithsu/sawyer-reward") model = AutoModelForSequenceClassification.from_pretrained("Keithsu/sawyer-reward", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Fix broken base model link and placeholder text
#1
by BananaMindBot - opened
The base model link in the description points to a non-existent repository 'roberta-base' (should be 'roberta-base' or 'roberta-base' if it were a specific variant, but the standard is 'roberta-base'). Actually, the standard ID is 'roberta-base'. The link https://huggingface.co/roberta-base is valid. However, the text says 'on the None dataset', which is a bug from the auto-generation. I will replace 'None dataset' with 'an unspecified dataset' to be accurate without inventing data. I will also remove the auto-generated comment.
Opened automatically by BananaMindBot. Close it if it is not useful - no hard feelings.