
This repo contains a low-rank adapter for LLaMA-13b fit on the Stanford Alpaca dataset.

### How to use (8-bit)

```python
import torch
from peft import PeftModel
from transformers import LlamaTokenizer, LlamaForCausalLM, GenerationConfig

tokenizer = LlamaTokenizer.from_pretrained("decapoda-research/llama-13b-hf")
model = LlamaForCausalLM.from_pretrained(
        "decapoda-research/llama-13b-hf",
        load_in_8bit=True,
        torch_dtype=torch.float16,
        device_map="auto",
)
model = PeftModel.from_pretrained(
    model, "baruga/alpaca-lora-13b",
    torch_dtype=torch.float16
)
```

For further information, check out this Github repo: https://github.com/tloen/alpaca-lora.
{"license": "mit", "datasets": ["tatsu-lab/alpaca"]}
dataset:tatsu-lab/alpaca license:mit region:us
TAGS
#dataset-tatsu-lab/alpaca #license-mit #region-us 


This repo contains a low-rank adapter for LLaMA-13b fit on the Stanford Alpaca dataset.

### How to use (8-bit)



For further information, check out this Github repo: URL
### How to use (8-bit)



For further information, check out this Github repo: URL
TAGS
#dataset-tatsu-lab/alpaca #license-mit #region-us 
 ### How to use (8-bit)



For further information, check out this Github repo: URL
TAGS
#dataset-tatsu-lab/alpaca #license-mit #region-us 
### How to use (8-bit)



For further information, check out this Github repo: URL