Instructions to use allenai/Llama-3.1-Tulu-3-8B-DPO-RM-RB2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allenai/Llama-3.1-Tulu-3-8B-DPO-RM-RB2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="allenai/Llama-3.1-Tulu-3-8B-DPO-RM-RB2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("allenai/Llama-3.1-Tulu-3-8B-DPO-RM-RB2") model = AutoModelForSequenceClassification.from_pretrained("allenai/Llama-3.1-Tulu-3-8B-DPO-RM-RB2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53d00889879925379f927464ee35e38fedc796b6894a81edaf7ad8161d983da8
- Size of remote file:
- 4.98 GB
- SHA256:
- 3cb7eccc1c8c9263a641782c694e5c9e67709ea343fd6d9e170024590012c5b9
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