Instructions to use bidit/lamma2-mycode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bidit/lamma2-mycode 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, "bidit/lamma2-mycode") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from bidit/lamma2-mycode: direct link, hf CLI and curl.
- Browser
- Download file 16.8 MB
-
https://huggingface.co/bidit/lamma2-mycode/resolve/main/adapter_model.bin
- Command line
-
hf download hf://bidit/lamma2-mycode/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/bidit/lamma2-mycode/resolve/main/adapter_model.bin
16.8 MB
- Xet hash:
- d204b1afd9193f6e09b04d9c6b87f8c946cf403b0110827613658f244f831778
- Size of remote file:
- 16.8 MB
- SHA256:
- 0492a6de85f55f484d1b39d859a8b0ae9de949dcb45cc128379e9b79520fa5df
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