Token Classification
Transformers
Safetensors
qwen2
Generated from Trainer
trl
prm
text-generation-inference
Instructions to use alothomas/Qwen2.5-3B-PRM-RAD-balanced-V3 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-V3 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-V3")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("alothomas/Qwen2.5-3B-PRM-RAD-balanced-V3") model = AutoModelForTokenClassification.from_pretrained("alothomas/Qwen2.5-3B-PRM-RAD-balanced-V3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20bf27004a3a019a269ae4fec8c76d275800f9035b902918fed612ec33f3537f
- Size of remote file:
- 5.56 kB
- SHA256:
- d6c61268ccfdff42a281550d56e732098c67400892d704118394669ab0ca4b61
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