Instructions to use baltop/deep_500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use baltop/deep_500 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-6.7b-instruct") model = PeftModel.from_pretrained(base_model, "baltop/deep_500") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d9a7cd684c37033f834b0232a438a1e09ab4dd3d84e1b31e3a0a2e53d858040
- Size of remote file:
- 81.8 MB
- SHA256:
- 718ae128457a2e833ea6407d4ede56133227b60c2403ba8d2af9b3c5ced95c72
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