FreedomIntelligence/sharegpt-deutsch
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How to use LSX-UniWue/LLaMmlein_1B_chat_sharegpt with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("LSX-UniWue/LLaMmlein_1b")
model = PeftModel.from_pretrained(base_model, "LSX-UniWue/LLaMmlein_1B_chat_sharegpt")This is a chat adapter for the German Tinyllama 1B language model. Find more details on our page and our preprint! We also merged the adapter and converted it to GGUF here.
import torch
from peft import PeftConfig, PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
torch.manual_seed(42)
# script config
base_model_name = "LSX-UniWue/LLaMmlein_1B"
chat_adapter_name = "LSX-UniWue/LLaMmlein_1B_chat_sharegpt"
device = "cuda" # or mps
# chat history
messages = [
{
"role": "user",
"content": """Na wie geht's?""",
},
]
# load model
config = PeftConfig.from_pretrained(chat_adapter_name)
base_model = model = AutoModelForCausalLM.from_pretrained(
base_model_name,
torch_dtype=torch.bfloat16,
device_map=device,
)
base_model.resize_token_embeddings(32064)
model = PeftModel.from_pretrained(base_model, chat_adapter_name)
tokenizer = AutoTokenizer.from_pretrained(chat_adapter_name)
# encode message in "ChatML" format
chat = tokenizer.apply_chat_template(
messages,
return_tensors="pt",
add_generation_prompt=True,
).to(device)
# generate response
print(
tokenizer.decode(
model.generate(
chat,
max_new_tokens=300,
pad_token_id=tokenizer.pad_token_id,
eos_token_id=tokenizer.eos_token_id,
)[0],
skip_special_tokens=False,
)
)
Base model
LSX-UniWue/LLaMmlein_1B