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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5cd3b6c5b414fd76ace7778000c683b43d33938f16d0e4c61131d05b73c7fbf8
- Size of remote file:
- 4.96 GB
- SHA256:
- 9112783b8817b4792055c5b26df8ab33eee78f5b547ee3e3c141bf6c07aa1d9e
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