Instructions to use Sakuna/LLaMaCoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Sakuna/LLaMaCoder 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, "Sakuna/LLaMaCoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b473e7ec2670bbd7aaf3fe95018837f46ad51cf5061499e93fba9097dbc1cc88
- Size of remote file:
- 134 MB
- SHA256:
- 06432653361ff1fed251f11785ddbd19c45d2f708e96676994cdfbed34e67054
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