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We profile the GPU memory and training speed of both LoRA (LoRA (emb) refers to training the embedding and output layer, while LoRA has no trainable embedding and output layer) and Q-LoRA in the setup of single-GPU training. In this test, we experiment on a single A100-SXM4-80G GPU, and we... | https://github.com/QwenLM/Qwen | -1 | [
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https://raw.githubusercontent.com/QwenLM/Qwen/main/README.md | [
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... | vLLM
For deployment and fast inference, we suggest using vLLM.
If you use cuda 12.1 and pytorch 2.1, you can directly use the following command to install vLLM.
```bash
| https://github.com/QwenLM/Qwen | -1 | [
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] | pip install vllm | https://github.com/QwenLM/Qwen | 0 | [
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https://raw.githubusercontent.com/QwenLM/Qwen/main/README.md | [
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git clone https://github.com/QwenLM/vllm-gptq
cd vllm-gptq
pip install -e .
```
Otherwise, please refer to the official vLLM [Installation Instructions](https://docs.vllm.ai/en/latest/getting_started/ins... | https://github.com/QwenLM/Qwen | 0 | [
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... | vLLM + Web Demo / OpenAI-like API
You can use FastChat to lauch a web demo or an OpenAI API server. First, install FastChat:
```bash
pip install "fschat[model_worker,webui]"
```
To run Qwen with vLLM and FastChat, you need launch a controller by:
```bash
python -m fastchat.serve.controller
```
Then you can launch t... | https://github.com/QwenLM/Qwen | 0 | [
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We provide code for users to build a web UI demo (thanks to @wysaid). Before you start, make sure you install the following packages:
```
pip install -r requirements_web_demo.txt
```
Then run the command below and click on the generated link:
```bash
python web_demo.py
```
<p align="center">
<br>
<i... | https://github.com/QwenLM/Qwen | 0 | [
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We provide methods to deploy local API based on OpenAI API (thanks to @hanpenggit). Before you start, install the required packages:
```bash
pip install fastapi uvicorn "openai<1.0" pydantic sse_starlette
```
Then run the command to deploy your API:
```bash
python openai_api.py
```
You can change your argument... | https://github.com/QwenLM/Qwen | 0 | [
"chinese",
"flash-attention",
"large-language-models",
"llm",
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https://raw.githubusercontent.com/QwenLM/Qwen/main/README.md | [
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To simplify the deployment process, we provide docker images with pre-built environments: [qwenllm/qwen](https://hub.docker.com/r/qwenllm/qwen). You only need to install the driver and download model files to launch demos, deploy OpenAI API, and finetune the model.
| https://github.com/QwenLM/Qwen | -1 | [
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1. Install the correct version of Nvidia driver depending on the image to use:
- `qwenllm/qwen:cu117` (**recommend**): `>= 515.48.07`
- `qwenllm/qwen:cu114` (w/o flash-attention): `>= 470.82.01`
- `qwenllm/qwen:cu121`: `>= 530.30.02`
- `qwenllm/qwen:latest`: same as `qwenllm/qwen:cu117`
2. Install... | https://github.com/QwenLM/Qwen | 1 | [
"chinese",
"flash-attention",
"large-language-models",
"llm",
"natural-language-processing",
"pretrained-models"
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https://raw.githubusercontent.com/QwenLM/Qwen/main/README.md | [
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] | test if docker is correctly installed
sudo docker run hello-world
| https://github.com/QwenLM/Qwen | -1 | [
"chinese",
"flash-attention",
"large-language-models",
"llm",
"natural-language-processing",
"pretrained-models"
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https://raw.githubusercontent.com/QwenLM/Qwen/main/README.md | [
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sudo docker run --rm --runtime=nvidia --gpus all ubuntu nvidia-smi
```
3. Download model checkpoints and codes to your environment (see [here](#DownloadModel)).
| https://github.com/QwenLM/Qwen | 1 | [
"chinese",
"flash-attention",
"large-language-models",
"llm",
"natural-language-processing",
"pretrained-models"
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https://raw.githubusercontent.com/QwenLM/Qwen/main/README.md | [
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"checkpoint_path=/pa... | Deployment
Here we use Qwen-7B-Chat as an example. Before launching a web demo or API, you can setup the configuration as shown below:
```bash
IMAGE_NAME=qwenllm/qwen:cu117
PORT=8901
CHECKPOINT_PATH=/path/to/Qwen-7B-Chat | https://github.com/QwenLM/Qwen | -1 | [
"chinese",
"flash-attention",
"large-language-models",
"llm",
"natural-language-processing",
"pretrained-models"
] |
https://raw.githubusercontent.com/QwenLM/Qwen/main/README.md | [
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"... | Finetuning
The method of finetuning using the pre-built Docker image is basically the same as [the above chapter](#Finetuning) (we have already installed dependencies in the image):
The following is an example of single-GPU LoRA:
```bash
IMAGE_NAME=qwenllm/qwen:cu117
CHECKPOINT_PATH=/path/to/Qwen-7B | https://github.com/QwenLM/Qwen | -1 | [
"chinese",
"flash-attention",
"large-language-models",
"llm",
"natural-language-processing",
"pretrained-models"
] |
https://raw.githubusercontent.com/QwenLM/Qwen/main/README.md | [
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Qwen-Chat has been optimized for tool usage and function calling capabilities. Users can develop agents, LangChain applications, and even augment Qwen with a Python Code Interpreter.
We provide documentation on how to implement tool calls based on the principle of ReAct Prompting, please refer to [the ReAc... | https://github.com/QwenLM/Qwen | -1 | [
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... | Table of Contents
Please note that the `Readme.md` file is a Markdown (`.md`) file. If you have downloaded this code bundle from the Manning website and are viewing it on your local computer, I recommend using a Markdown editor or previewer for proper viewing. If you haven't installed a Markdown editor yet, [MarkText]... | https://github.com/rasbt/LLMs-from-scratch | -1 | [
"chatgpt",
"gpt",
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"python",
"pytorch"
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WebLLM works as a companion project of [MLC LLM](https://github.com/mlc-ai/mlc-llm).
It reuses the model artifact and builds flow of MLC LLM, please check out
[MLC LLM document](https://llm.mlc.ai/docs/deploy/javascript.html)
on how to add new model weights and libraries to WebLLM.
Here, we g... | https://github.com/mlc-ai/web-llm | -1 | [
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"language-model",
"llm",
"tvm",
"webgpu",
"webml"
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NOTE: you don't need to build by yourself unless you would
like to change the WebLLM package, follow [use WebLLM](#use-web-llm-package) instead.
WebLLM package is a web runtime designed for [MLC LLM](https://github.com/mlc-ai/mlc-llm).
1. Install all the prerequisites for compilation... | https://github.com/mlc-ai/web-llm | -1 | [
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"deep-learning",
"language-model",
"llm",
"tvm",
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... | Installation
The easiest way to install Nebuly’s SDK is via `pip`:
```
pip install nebuly
```
Once installed, authenticate to Nebuly platform and start building.
| https://github.com/nebuly-ai/nebuly | 0 | [
"ai",
"analytics",
"artificial-intelligence",
"deeplearning",
"large-language-models",
"llm"
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我们对中文微调的模型参数进行了量化，方便以更少的计算资源运行。目前已经在[Hugging Face](https://huggingface.co/FlagAlpha)上传了13B中文微调模型[FlagAlpha/Llama2-Chinese-13b-Chat](https://huggingface.co/FlagAlpha/Llama2-Chinese-13b-Chat)的4bit压缩版本[FlagAlpha/Llama2-Chinese-13b-Chat-4bit](https://huggingface.co/FlagAlpha/Llama2-Chinese-13b-Chat-4bit)，具体调用方式如下：
... | https://github.com/LlamaFamily/Llama2-Chinese | 0 | [
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Usage: openllm [OPTIONS] COMMAND [ARGS]...
██████╗ ██████╗ ███████╗███╗ ██╗██╗ ██╗ ███╗ ███╗
██╔═══██╗██╔══██╗██╔════╝████╗ ██║██║ ██║ ████╗ ██... | https://github.com/bentoml/OpenLLM | 0 | [
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<!-- update-readme.py: start -->
<details>
<summary>Baichuan</summary>
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Llama-recipes offers the installation of optional packages. There are three optional dependency groups.
To run the unit tests we can install the required dependencies with:
```
pip install --extra-index-url https://download.pytorch.org/whl/test/cu118 llama-recipes[tests]
```
For the v... | https://github.com/facebookresearch/llama-recipes | 0 | [
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To install from source e.g. for development use these commands. We're using hatchling as our build backend which requires an up-to-date pip as well as setuptools package.
```
git clone git@github.com:facebookresearch/llama-recipes.git
cd llama-recipes
pip install -U pip setuptools
pip install --extr... | https://github.com/facebookresearch/llama-recipes | 0 | [
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Given that the original checkpoint resides under models/7B you can install all requirements and convert the checkpoint with:
```bash
| https://github.com/facebookresearch/llama-recipes | -1 | [
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pip freeze | grep transformers | https://github.com/facebookresearch/llama-recipes | 2 | [
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git clone git@github.com:huggingface/transformers.git
cd transformers
pip install protobuf
python src/transformers/models/llama/convert_llama_weights_to_hf.py \
--input_dir /path/to/downloaded/llama/weights --model_size 7B --output_dir /output/path
```
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All the parameters in the examples and recipes below need to be further tuned to have desired results based on the model, method, data and task at hand.
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This repository is organized in the following way:
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[configs](src/llama_recipes/configs/): Contains the configuration files for PEFT methods, FSDP, Datasets.
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To get started quickly, you can use a pre-built development environment. **Click the button below** to open the repo in GitHub Codespaces, and then continue the readme!
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pf flow init --flow ./my_chatbot --type chat
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We also offer a VS Code extension (a flow designer) for an interactive flow development experience with UI.
<img src="examples/tutorials/quick-start/media/vsc.png" alt="vsc" width="1000"/>
You can install it from the <a href="https://marketplace.visualstudio.com/items?itemName=prompt-flow.prompt-fl... | https://github.com/microsoft/promptflow | -1 | [
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[Getting started with prompt flow](./docs/cloud/azureai/quick-start/index.md): A step by step guidance to invoke your first flow run.
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[Tutorial: Chat with PDF](https://github.com/microsoft/promptflow/blob/main/examples/tutorials/e2e-development/chat-with-pdf.md): An end-to-end tutorial on how to build a high quality chat application with prompt flow, including flow development and evaluation with metrics.
> More examples can be ... | https://github.com/microsoft/promptflow | 2 | [
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```shell
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],
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"let try parse file ."
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] | -> jq has been successfully installed. Let me try to parse the file again.
| https://github.com/TheR1D/shell_gpt | -1 | [
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"runtime configuration file setup parameter runtime configuration file ` ~/.config/... | Runtime configuration file
You can setup some parameters in runtime configuration file `~/.config/shell_gpt/.sgptrc`:
```text
| https://github.com/TheR1D/shell_gpt | -1 | [
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https://raw.githubusercontent.com/continuedev/continue/main/README.md | [
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[
"getting",
"started"
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[
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]
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| https://github.com/continuedev/continue | -1 | [
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"... | [
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"... | Download for [VS Code](https://marketplace.visualstudio.com/items?itemName=Continue.continue) and [JetBrains](https://plugins.jetbrains.com/plugin/22707-continue-extension)
You can try out Continue for free using a proxy server that securely makes calls with our API key to models like GPT-4, Gemini Pro, and Phind Code... | https://github.com/continuedev/continue | -1 | [
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