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# Load the model.
# Note: It can take a while to download LLaMA and add the adapter modules.
# You can also use the 13B model by loading in 4bits.
import torch
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer, LlamaTokenizer, StoppingCriteria, StoppingCriteriaList, TextIteratorStreamer
model_name = "baffo32/decapoda-research-llama-7b-hf"
adapters_name = 'timdettmers/guanaco-7b'
print(f"Starting to load the model {model_name} into memory")
m = AutoModelForCausalLM.from_pretrained(
model_name,
#load_in_4bit=True,
torch_dtype=torch.bfloat16,
device_map={"": 0}
)
m = PeftModel.from_pretrained(m, adapters_name)
m = m.merge_and_unload()
tok = LlamaTokenizer.from_pretrained(model_name)
tok.bos_token_id = 1
stop_token_ids = [0]
print(f"Successfully loaded the model {model_name} into memory")