Instructions to use MaxJeblick/reward-model-deberta-v3-unit-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MaxJeblick/reward-model-deberta-v3-unit-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MaxJeblick/reward-model-deberta-v3-unit-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MaxJeblick/reward-model-deberta-v3-unit-test") model = AutoModelForSequenceClassification.from_pretrained("MaxJeblick/reward-model-deberta-v3-unit-test") - 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 sha256:800e32c529b09430037ede5d7d12667604ead1e63aeb9c8d1516bb971e539bcd
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size 6189204
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