ChatGLM Howto
ChatGLM is an open-source bilingual (Chinese-English) large language model series developed by Zhipu AI and Tsinghua KEG, featuring smooth dialogue capabilities and low deployment thresholds.
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Install required packages: Install the necessary Python packages by running: pip install protobuf transformers==4.30.2 cpm_kernels torch>=2.0 gradio mdtex2html sentencepiece accelerate
Import the model and tokenizer: Use the following code to import ChatGLM:
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda()
Generate a response: Generate a response by calling the chat method:
response, history = model.chat(tokenizer, "你好", history=[])
print(response)
Continue the conversation: To continue the conversation, pass the history to subsequent calls:
response, history = model.chat(tokenizer, "晚上睡不着应该怎么办", history=history)
print(response)
Use the web interface: For a more user-friendly experience, visit https://chatglm.cn to use the web interface of the larger ChatGLM model
Download mobile app: Scan the QR code on the ChatGLM website to download the mobile app for iOS or Android
ChatGLM FAQs
ChatGLM is an open bilingual language model based on the General Language Model (GLM) framework. It is trained on both Chinese and English data and optimized for question-answering and dialogue tasks.
ChatGLM Monthly Traffic Trends
ChatGLM saw a slight 0.0% decline in traffic, with a reduction of 401 visits. Despite the lack of direct product updates, the model's advanced capabilities and multilingual pre-training on 10 trillion tokens suggest it remains a robust AI product. However, the absence of recent updates or notable market activities might indicate a period of stability rather than active growth.
View history traffic
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