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:
- f3685d5e0abd10139639b2fa62a19052b1f0b5330d4333f80558fb5d19db1957
- Size of remote file:
- 6.52 kB
- SHA256:
- e2d64cf27d0452b8d67c4245bb68715145f5d6adc64bf717382005aeb66fafe6
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