Komodo_6B_v3.0.0:可在昇腾Ascend310/910处理器上进行文本生成任务，适配昇腾环境，提供推理测试脚本，支持PyTorch框架，便于快速部署和使用。【此简介由AI生成】

1、适配昇腾处理器：Ascend310、Ascend910系列 2、开发环境：Ascend-cann-toolkit_xxx、Ascend-cann-kernels-xxx(可选)、python3.8 3、下载代码：git clone https://modelers.cn/ShanXi/Komodo_6B_v3.0.0.git 4、安装依赖：pip install -r examples/requirements.txt 5、推理测试：python examples/inference.py 6、推理脚本：

import argparse import torch from openmind import pipeline, is_torch_npu_available from transformers import AutoTokenizer, AutoModelForCausalLM from openmind_hub import snapshot_download

def parse_args():
    parser = argparse.ArgumentParser()
    parser.add_argument("--model_name_or_path",type=str,help="模型路径",default="./",)
    args = parser.parse_args()
    return args


if is_torch_npu_available():
    device = "npu:0"
else:
    device = "cpu"


args = parse_args()
if args.model_name_or_path:
    model_path = args.model_name_or_path
else:
    model_path = snapshot_download('ShanXi/Komodo_6B_v3.0.0',revision='main',resume_donwload=True,ignore_patterns=['*.h5','*.ot','*.msgpack'])
model = AutoModelForCausalLM.from_pretrained(model_path)
tokenizer = AutoTokenizer.from_pretrained(model_path)


text = '''<|system|>
당신은 사용자의 질문에 친절하게 답변을 하는 챗봇입니다.
<|user|>
안녕하세요?
<|bot|>
'''
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=20)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

import argparse import torch from openmind import pipeline, is_torch_npu_available from transformers import AutoTokenizer, AutoModelForCausalLM from openmind_hub import snapshot_download

def parse_args():
    parser = argparse.ArgumentParser()
    parser.add_argument("--model_name_or_path",type=str,help="模型路径",default="./",)
    args = parser.parse_args()
    return args


if is_torch_npu_available():
    device = "npu:0"
else:
    device = "cpu"


args = parse_args()
if args.model_name_or_path:
    model_path = args.model_name_or_path
else:
    model_path = snapshot_download('ShanXi/Komodo_6B_v3.0.0',revision='main',resume_donwload=True,ignore_patterns=['*.h5','*.ot','*.msgpack'])
model = AutoModelForCausalLM.from_pretrained(model_path)
tokenizer = AutoTokenizer.from_pretrained(model_path)


text = '''<|system|>
당신은 사용자의 질문에 친절하게 답변을 하는 챗봇입니다.
<|user|>
안녕하세요?
<|bot|>
'''
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=20)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))