Chinese-LLaMA-2-13B

Linly-Chinese-LLaMA2 基于 LLaMA2进行中文化训练，使用课程学习方法跨语言迁移，词表针对中文重新设计，数据分布更均衡，收敛更稳定。

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 = "北京有什么好玩的地方？"

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)