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:
- bc060b57823f4a651ac8e5cca60c6a8e159ccde52a24312920b5e83e0c7210af
- Size of remote file:
- 4.93 GB
- SHA256:
- 4f694985cdcca3c4ae347468d7eafca41ce946ef2403de9dac50d1c90ead3e3d
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