Token Classification
Transformers
Safetensors
qwen2
Generated from Trainer
trl
stepwise-reward-trainer
text-generation-inference
Instructions to use plaguss/Qwen2.5-0.5B-Math-Shepherd-PRM-token-0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use plaguss/Qwen2.5-0.5B-Math-Shepherd-PRM-token-0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="plaguss/Qwen2.5-0.5B-Math-Shepherd-PRM-token-0.1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("plaguss/Qwen2.5-0.5B-Math-Shepherd-PRM-token-0.1") model = AutoModelForTokenClassification.from_pretrained("plaguss/Qwen2.5-0.5B-Math-Shepherd-PRM-token-0.1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d19f30805fa42c2b2d8486cdee556c9b8cf02771c909f90ab8af9834c7e7b56
- Size of remote file:
- 6.71 kB
- SHA256:
- f5c9fb5d6f55594f9a644c5b3c5d127ed6e34e3926c7a248a4cf0f9769c78018
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