max_new_tokens 是一个更推荐的参数,用于直接指定生成文本中新增 token 的最大数量。相比 max_length,它能更灵活地控制生成内容的长度,避免因默认值过小而导致生成内容被截断。 操作步骤: 在调用模型生成文本时,显式设置 max_new_tokens 参数。例如: output = model.generate( input_ids, max_new_tokens=50, ...
output_texts = model.generate( input_ids=input_ids, attention_mask=attention_mask, pad_token_id= tokenizer.eos_token_id, eos_token_id= tokenizer.eos_token_id, max_new_tokens=500, do_sample=False, top_k=30, top_p=0.85, temperature=0.3, repetition_penalty=1.2) ...
函数名:build_model_input 函数传入参数: model_tokenizer:模型tokenizer,由平台从上传的模型中加载; messages:用户调用会话模型服务时传入的会话信息,当为会话模式时生效; kwargs:其他参数,目前未使用。当未来功能升级时,做向前兼容使用。 函数输出结果: token_ids: 转换后的一维token id数组,将用于喂入模型 样例...
responses = model.generate("Write quick sort code in python", do_sample=True, temperature=0.6, num_beams=4, top_k=50, top_p=0.95, max_new_tokens=512) 评估基线数据集(Benchmark) 数据集评估结果参考 任务验证集模型昇腾值参考值社区值
(text) input_ids = tokenizer(text, return_tensors="pt").to("cuda") outputs = model.generate(**input_ids, max_new_tokens=1000) response = tokenizer.decode(outputs[0])print("FC Invoke End RequestId: "+ request_id)returnstr(response) +"\n"if__name__ =='__main__': app.run(...
(image_file) image = Image.open(BytesIO(response.content)).convert('RGB') else: image = Image.open(image_file).convert('RGB') return image model_path="liuhaotian/LLaVA-Lightning-MPT-7B-preview" model_base=None load_8bit=False load_4bit=False temperature = 0.2 max_new_tokens = 512 ...
the model will take a set of text messages as the input and generate a summary as the output. You need to format the data as a prompt (the messages) with a correct response (the summary). You also need to chunk examples into longer input seque...
In the first two posts of this series we have developed an Outlook add-in that, using the Open AI models, helps users to generate professional business mails...
object isstructureddifferentlythantheAPI'slayout results object, there isn't a clear way to generate the required ocr.json filesstrictlyusing thePython SDK.Thisblog post delves into the custom solution wedevelopedtomanually code this process, addressing a common problem discus...
["input_ids"] # 首次调用model.generate()进行推理将包含图编译时间,推理性能显示不准确,多次重复调用以获取准确的推理性能 outputs = model.generate(inputs, max_new_tokens=30, do_sample=False) response = tokenizer.decode(outputs) print(response) # ['<s>I love Beijing, because it’...