Instructions to use ddxdaniel/reward-model-gl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ddxdaniel/reward-model-gl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ddxdaniel/reward-model-gl")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ddxdaniel/reward-model-gl") model = AutoModelForSequenceClassification.from_pretrained("ddxdaniel/reward-model-gl") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:619a5cb3938cca4989525e7d0133eb91d819761c278cecf324e86e3980d40d1b
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size 3096176248
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