Instructions to use chaimag/ko-llama-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use chaimag/ko-llama-7B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "chaimag/ko-llama-7B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e37d4b6760d2bc9aefb95111b0691e8cfcb8e4d9bd465ba02c920b24d78baf38
- Size of remote file:
- 134 MB
- SHA256:
- 3026c1c5edc6e292e8e07c54ad3ed69b64bb473b938ceebfe98295a627cb0e49
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