Instructions to use yuanzhoulvpi/chatglm6b-dddd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yuanzhoulvpi/chatglm6b-dddd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="yuanzhoulvpi/chatglm6b-dddd", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yuanzhoulvpi/chatglm6b-dddd", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use yuanzhoulvpi/chatglm6b-dddd with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "yuanzhoulvpi/chatglm6b-dddd" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yuanzhoulvpi/chatglm6b-dddd", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/yuanzhoulvpi/chatglm6b-dddd
- SGLang
How to use yuanzhoulvpi/chatglm6b-dddd with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "yuanzhoulvpi/chatglm6b-dddd" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yuanzhoulvpi/chatglm6b-dddd", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "yuanzhoulvpi/chatglm6b-dddd" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yuanzhoulvpi/chatglm6b-dddd", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use yuanzhoulvpi/chatglm6b-dddd with Docker Model Runner:
docker model run hf.co/yuanzhoulvpi/chatglm6b-dddd
YAML Metadata Warning:The pipeline tag "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
介绍: chatglm6b-dddd叫chatglm6b等等弟弟
chatglm6b官方更新的代码太快了,并不知道官方的代码会不会有什么bug,而且还需要基于官方的代码做二次修改,简直是跟不起~- 因此,维护一个我自己使用的版本,保证自己使用lora微调版本跑起来没问题。
安装依赖
pip install protobuf==3.20.0 transformers==4.26.1 icetk cpm_kernels
更多信息,可以查看这个链接:https://github.com/yuanzhoulvpi2017/zero_nlp/tree/main/simple_thu_chatglm6b
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