Token Classification
Transformers
Safetensors
llama
Generated from Trainer
trl
stepwise-reward-trainer
text-generation-inference
Instructions to use plaguss/Llama-3.1-8B-Math-Shepherd-PRM-0.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use plaguss/Llama-3.1-8B-Math-Shepherd-PRM-0.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="plaguss/Llama-3.1-8B-Math-Shepherd-PRM-0.2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("plaguss/Llama-3.1-8B-Math-Shepherd-PRM-0.2") model = AutoModelForTokenClassification.from_pretrained("plaguss/Llama-3.1-8B-Math-Shepherd-PRM-0.2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e35984747436b746338bef83e9c2ac833054c94dc943e9cabc48a1807561a1d9
- Size of remote file:
- 6.78 kB
- SHA256:
- 85cecfbdfb2de12814ce3161de3761a26c3788b6844ef118309547237a377d1b
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