Instructions to use rediska0123/llama3.18binstruct-sciqa-lora-correctness-2epochs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rediska0123/llama3.18binstruct-sciqa-lora-correctness-2epochs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="rediska0123/llama3.18binstruct-sciqa-lora-correctness-2epochs", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("rediska0123/llama3.18binstruct-sciqa-lora-correctness-2epochs", trust_remote_code=True) model = AutoModel.from_pretrained("rediska0123/llama3.18binstruct-sciqa-lora-correctness-2epochs", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4d46bb61dfd6c17cf75484aedf16928ccde6c0c7fc0359879fceb6cdfe16aa1
- Size of remote file:
- 11.4 MB
- SHA256:
- 2f87f84cd744477c28ec88506449627f5caff7040f3cd320bc0f4f2b8de36279
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