
# This is a private NLP model trained with data from SequioaDB

```
import torch
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig

model_name = "TinyPixel/Llama-2-7B-bf16-sharded"
adapters_name = 'wangzhang/Llama2-sequoiaDB'

model = AutoModelForCausalLM.from_pretrained(
    model_name,
    load_in_4bit=True,
    torch_dtype=torch.bfloat16,
    device_map="auto",
    max_memory= {i: '24000MB' for i in range(torch.cuda.device_count())},
    quantization_config=BitsAndBytesConfig(
        load_in_4bit=True,
        bnb_4bit_compute_dtype=torch.bfloat16,
        bnb_4bit_use_double_quant=True,
        bnb_4bit_quant_type='nf4'
    ),
)
model = PeftModel.from_pretrained(model, adapters_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
```
{"library_name": "adapter-transformers", "tags": ["autotrain", "text-generation"], "datasets": ["wangzhang/sdb"], "widget": [{"text": "This is a private NLP model trained with data from SequioaDB"}]}
adapter-transformers tensorboard autotrain text-generation dataset:wangzhang/sdb region:us