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README.md
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These files are GGML format model files for [THUDM's chatglm2 6B](https://huggingface.co/THUDM/chatglm2-6b).
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GGML files are for CPU + GPU inference using [chatglm.cpp](https://github.com/li-plus/chatglm.cpp) and
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# Prompt template
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**NOTE**: prompt template is not available yet since the system prompt is hard coded in chatglm.cpp for now.
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| chatglm2-ggml-q8_0.bin | q8_0 | 8 | 6.6 GB |
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# How to run in
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# Slack
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For further support, and discussions on these models and AI in general, join our [slack channel](https://join.slack.com/t/xorbitsio/shared_invite/zt-1o3z9ucdh-RbfhbPVpx7prOVdM1CAuxg)!
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These files are GGML format model files for [THUDM's chatglm2 6B](https://huggingface.co/THUDM/chatglm2-6b).
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GGML files are for CPU + GPU inference using [chatglm.cpp](https://github.com/li-plus/chatglm.cpp) and [Xorbits Inference](https://github.com/xorbitsai/inference).
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# Prompt template
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**NOTE**: prompt template is not available yet since the system prompt is hard coded in chatglm.cpp for now.
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| chatglm2-ggml-q8_0.bin | q8_0 | 8 | 6.6 GB |
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# How to run in Xorbits Inference
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## Install
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Xinference can be installed via pip from PyPI. It is highly recommended to create a new virtual environment to avoid conflicts.
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```bash
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$ pip install "xinference[all]"
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$ pip install chatglm-cpp
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```
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## Start Xorbits Inference
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To start a local instance of Xinference, run the following command:
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```bash
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$ xinference
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```
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Once Xinference is running, an endpoint will be accessible for model management via CLI or Xinference client. The default endpoint is `http://localhost:9997`. You can also view a web UI using the Xinference endpoint to chat with all the builtin models. You can even chat with two cutting-edge AI models side-by-side to compare their performance!
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# Slack
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For further support, and discussions on these models and AI in general, join our [slack channel](https://join.slack.com/t/xorbitsio/shared_invite/zt-1o3z9ucdh-RbfhbPVpx7prOVdM1CAuxg)!
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