Text Classification
Transformers
Safetensors
qwen2
trl
reward-trainer
Generated from Trainer
text-embeddings-inference
Instructions to use trl-lib/Qwen2-0.5B-Reward with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trl-lib/Qwen2-0.5B-Reward with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="trl-lib/Qwen2-0.5B-Reward")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("trl-lib/Qwen2-0.5B-Reward") model = AutoModelForSequenceClassification.from_pretrained("trl-lib/Qwen2-0.5B-Reward") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98979eb84574769e02857674d99b2e39384e6b51350fc23bb93e69fc6313cb29
- Size of remote file:
- 5.24 kB
- SHA256:
- a56f657b0820015fb3d9eeffd7193b370e0029b9f4fb1a9ce77bb75e184f10ec
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