Text Classification
Transformers
TensorBoard
Safetensors
deberta-v2
trl
reward-trainer
Generated from Trainer
text-embeddings-inference
Instructions to use MahmoudMohamed/Reward_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MahmoudMohamed/Reward_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MahmoudMohamed/Reward_Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MahmoudMohamed/Reward_Model") model = AutoModelForSequenceClassification.from_pretrained("MahmoudMohamed/Reward_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a25388d795acd76008fe6cad5ca3f60acd2cc7a20f7aa1d452a489defab2532a
- Size of remote file:
- 11.1 kB
- SHA256:
- 6b00b6493b5f930d96744fd0fb4e6a447a29057ee087192ab57b41686f9aae22
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