Instructions to use Jennny/llama3_8b_helpsteer_coherence_rm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jennny/llama3_8b_helpsteer_coherence_rm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jennny/llama3_8b_helpsteer_coherence_rm")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jennny/llama3_8b_helpsteer_coherence_rm") model = AutoModelForSequenceClassification.from_pretrained("Jennny/llama3_8b_helpsteer_coherence_rm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b98c3173879560a62c8c3b2f63b7a1699d3feb403b75a718c6d56efab25b3c6
- Size of remote file:
- 17.2 MB
- SHA256:
- 4b2c8e50af20b1968e9f2d5fcfe9d79e8a10dc51863ca42a759c61d1f4c9ecb2
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