Token Classification
Transformers
PyTorch
Safetensors
qwen2
Generated from Trainer
axolotl
trl
prm
text-generation-inference
Instructions to use smohammadi/Qwen2.5-3B-MathShepherd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smohammadi/Qwen2.5-3B-MathShepherd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="smohammadi/Qwen2.5-3B-MathShepherd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("smohammadi/Qwen2.5-3B-MathShepherd") model = AutoModelForTokenClassification.from_pretrained("smohammadi/Qwen2.5-3B-MathShepherd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e8f4aceba415b35a4ba12a73dc2940d25173a0425ac234f90f8a636fa1ed9116
- Size of remote file:
- 988 MB
- SHA256:
- 75d308566846d7306686126e25339a9fb1486e79bb82ba4aa5c9293817f57ee0
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