Instructions to use ktm379/code-llama-7b-train_epoch3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ktm379/code-llama-7b-train_epoch3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyPixel/Llama-2-7B-bf16-sharded") model = PeftModel.from_pretrained(base_model, "ktm379/code-llama-7b-train_epoch3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0302c75717894be84e7dc01126f7cc775f79bf6776442bc6cd944cb4f5625ef
- Size of remote file:
- 4.86 kB
- SHA256:
- f0889cdea978b3f3b7d1233db2bb54db0e5fdfd1ea4e0f79f3305738873f9615
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