glm4

glm4 参数量

glm4 模型介绍

GLM4 Models

GLM 4 智谱 AI 模型，在语义、数学、推理、代码、知识等数据集的评测中，该模型都展现出了超越 Llama 3 8B 的优异表现。

GLM 4 模型包含了多语言支持，支持日文、韩文、德文等 26 种语言。

glm4 预训练模型：

可以从以下网址下载本文中使用的预训练模型 OneDrive or Tsinghua-Cloud.

通过 HuggingFace Hub 访问 GLM 模型

请安装 transformers>=4.23.1 并在此处查找所有可用模型。

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("THUDM/glm-10b", trust_remote_code=True)
model = AutoModelForSeq2SeqLM.from_pretrained("THUDM/glm-10b", trust_remote_code=True)
model = model.half().cuda()
model.eval()

# Inference
inputs = tokenizer("Ng is an adjunct professor at [MASK] (formerly associate professor and Director of its Stanford AI Lab or SAIL ). Also a pioneer in online education, Ng co-founded Coursera and deeplearning.ai.", return_tensors="pt")
inputs = tokenizer.build_inputs_for_generation(inputs, max_gen_length=512)
inputs = inputs.to('cuda')
outputs = model.generate(**inputs, max_length=512, eos_token_id=tokenizer.eop_token_id)
print(tokenizer.decode(outputs[0].tolist()))

# Training
inputs = tokenizer(
    ["Tsinghua University is located in [MASK].", "One minus one equals zero, is it correct? Answer: [MASK]"],
    return_tensors="pt", padding=True)
inputs = tokenizer.build_inputs_for_generation(inputs, targets=["Beijing", "No"], max_gen_length=8, padding=False)
inputs = inputs.to('cuda')
outputs = model(**inputs)
loss = outputs.loss
logits = outputs.logits

AI 扩展阅读：

• mytop 命令
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• rmmod 命令
• git 命令
• iostat 命令
• crash 命令
• npm 命令
• PHP 命令行 Commands
• uptime 命令
• users 命令

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