Token Classification
Transformers
Safetensors
qwen2
Generated from Trainer
trl
prm
text-generation-inference
Instructions to use alothomas/Qwen2.5-3B-PRM-RAD-balanced-150k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alothomas/Qwen2.5-3B-PRM-RAD-balanced-150k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="alothomas/Qwen2.5-3B-PRM-RAD-balanced-150k")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("alothomas/Qwen2.5-3B-PRM-RAD-balanced-150k") model = AutoModelForTokenClassification.from_pretrained("alothomas/Qwen2.5-3B-PRM-RAD-balanced-150k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14db8fffca0ce658ba921878922d9bcbbb408342cfdccde02ae97875fe333834
- Size of remote file:
- 4.98 GB
- SHA256:
- a325d9b0e1709a5a52343a9a61189319f5d989257d399cee5bf2e2937f2a39b9
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