Chinese-LLaMA-2-13B
Linly-Chinese-LLaMA2 ๅบไบ LLaMA2่ฟ่กไธญๆๅ่ฎญ็ป๏ผไฝฟ็จ่ฏพ็จๅญฆไน ๆนๆณ่ทจ่ฏญ่จ่ฟ็งป๏ผ่ฏ่กจ้ๅฏนไธญๆ้ๆฐ่ฎพ่ฎก๏ผๆฐๆฎๅๅธๆดๅ่กก๏ผๆถๆๆด็จณๅฎใ
่ฎญ็ป็ป่ๅbenchmarkๆๆ ่ฏฆ่ง ๐ป Github Repo
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("Linly-AI/Chinese-LLaMA-2-13B-hf", device_map="cuda:0", torch_dtype=torch.float16, trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("Linly-AI/Chinese-LLaMA-2-13B-hf", use_fast=False, trust_remote_code=True)
prompt = "ๅไบฌๆไปไนๅฅฝ็ฉ็ๅฐๆน๏ผ"
prompt = f"### Instruction:{prompt.strip()} ### Response:"
inputs = tokenizer(prompt, return_tensors="pt").to("cuda:0")
generate_ids = model.generate(inputs.input_ids, do_sample=True, max_new_tokens=2048, top_k=10, top_p=0.85, temperature=1, repetition_penalty=1.15, eos_token_id=2, bos_token_id=1, pad_token_id=0)
response = tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
response = response.lstrip(prompt)
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