Fix the docker image
This commit is contained in:
hiyouga 2024-06-11 00:19:17 +08:00
parent 0012762b04
commit 949e9908ad
4 changed files with 78 additions and 40 deletions

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@ -1,14 +1,44 @@
FROM nvcr.io/nvidia/pytorch:24.01-py3
# Use the NVIDIA official image with PyTorch 2.3.0
# https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel-24-02.html
FROM nvcr.io/nvidia/pytorch:24.02-py3
# Define installation arguments
ARG INSTALL_BNB=false
ARG INSTALL_VLLM=false
ARG INSTALL_DEEPSPEED=false
ARG PIP_INDEX=https://pypi.org/simple
# Set the working directory
WORKDIR /app
# Install the requirements
COPY requirements.txt /app/
RUN pip install -r requirements.txt
RUN pip config set global.index-url $PIP_INDEX
RUN python -m pip install --upgrade pip
RUN python -m pip install -r requirements.txt
# Copy the rest of the application into the image
COPY . /app/
RUN pip install -e .[metrics,bitsandbytes,qwen]
# Install the LLaMA Factory
RUN EXTRA_PACKAGES="metrics"; \
if [ "$INSTALL_BNB" = "true" ]; then \
EXTRA_PACKAGES="${EXTRA_PACKAGES},bitsandbytes"; \
fi; \
if [ "$INSTALL_VLLM" = "true" ]; then \
EXTRA_PACKAGES="${EXTRA_PACKAGES},vllm"; \
fi; \
if [ "$INSTALL_DEEPSPEED" = "true" ]; then \
EXTRA_PACKAGES="${EXTRA_PACKAGES},deepspeed"; \
fi; \
pip install -e .[$EXTRA_PACKAGES] && \
pip uninstall -y transformer-engine
# Set up volumes
VOLUME [ "/root/.cache/huggingface/", "/app/data", "/app/output" ]
# Expose port 7860 for the LLaMA Board
EXPOSE 7860
CMD [ "llamafactory-cli", "webui" ]
# Expose port 8000 for the API service
EXPOSE 8000

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@ -405,9 +405,9 @@ Please refer to [data/README.md](data/README.md) for checking the details about
Use the following 3 commands to run LoRA **fine-tuning**, **inference** and **merging** of the Llama3-8B-Instruct model, respectively.
```bash
CUDA_VISIBLE_DEVICES=0 llamafactory-cli train examples/lora_single_gpu/llama3_lora_sft.yaml
CUDA_VISIBLE_DEVICES=0 llamafactory-cli chat examples/inference/llama3_lora_sft.yaml
CUDA_VISIBLE_DEVICES=0 llamafactory-cli export examples/merge_lora/llama3_lora_sft.yaml
llamafactory-cli train examples/lora_single_gpu/llama3_lora_sft.yaml
llamafactory-cli chat examples/inference/llama3_lora_sft.yaml
llamafactory-cli export examples/merge_lora/llama3_lora_sft.yaml
```
See [examples/README.md](examples/README.md) for advanced usage (including distributed training).
@ -417,33 +417,33 @@ See [examples/README.md](examples/README.md) for advanced usage (including distr
### Fine-Tuning with LLaMA Board GUI (powered by [Gradio](https://github.com/gradio-app/gradio))
#### Use local environment
```bash
CUDA_VISIBLE_DEVICES=0 GRADIO_SHARE=1 llamafactory-cli webui
llamafactory-cli webui
```
</details>
#### Use Docker
### Build Docker
```bash
docker build -f ./Dockerfile -t llama-factory:latest .
docker run --gpus=all \
docker build -f ./Dockerfile \
--build-arg INSTALL_BNB=false \
--build-arg INSTALL_VLLM=false \
--build-arg INSTALL_DEEPSPEED=false \
--build-arg PIP_INDEX=https://pypi.org/simple \
-t llamafactory:latest .
docker run -it --gpus=all \
-v ./hf_cache:/root/.cache/huggingface/ \
-v ./data:/app/data \
-v ./output:/app/output \
-p 7860:7860 \
-p 8000:8000 \
--shm-size 16G \
--name llama_factory \
-d llama-factory:latest
--name llamafactory \
llamafactory:latest
```
#### Use Docker Compose
```bash
docker compose -f ./docker-compose.yml up -d
```
> [!TIP]
> Use Docker Compose to build image via `docker compose up -d`.
<details><summary>Details about volume</summary>

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@ -405,9 +405,9 @@ Docker 镜像:
下面三行命令分别对 Llama3-8B-Instruct 模型进行 LoRA **微调**、**推理**和**合并**。
```bash
CUDA_VISIBLE_DEVICES=0 llamafactory-cli train examples/lora_single_gpu/llama3_lora_sft.yaml
CUDA_VISIBLE_DEVICES=0 llamafactory-cli chat examples/inference/llama3_lora_sft.yaml
CUDA_VISIBLE_DEVICES=0 llamafactory-cli export examples/merge_lora/llama3_lora_sft.yaml
llamafactory-cli train examples/lora_single_gpu/llama3_lora_sft.yaml
llamafactory-cli chat examples/inference/llama3_lora_sft.yaml
llamafactory-cli export examples/merge_lora/llama3_lora_sft.yaml
```
高级用法请参考 [examples/README_zh.md](examples/README_zh.md)(包括多 GPU 微调)。
@ -417,31 +417,33 @@ CUDA_VISIBLE_DEVICES=0 llamafactory-cli export examples/merge_lora/llama3_lora_s
### LLaMA Board 可视化微调(由 [Gradio](https://github.com/gradio-app/gradio) 驱动)
#### 使用本地环境
```bash
CUDA_VISIBLE_DEVICES=0 GRADIO_SHARE=1 llamafactory-cli webui
llamafactory-cli webui
```
#### 使用 Docker
### 构建 Docker
```bash
docker build -f ./Dockerfile -t llama-factory:latest .
docker run --gpus=all \
docker build -f ./Dockerfile \
--build-arg INSTALL_BNB=false \
--build-arg INSTALL_VLLM=false \
--build-arg INSTALL_DEEPSPEED=false \
--build-arg PIP_INDEX=https://pypi.org/simple \
-t llamafactory:latest .
docker run -it --gpus=all \
-v ./hf_cache:/root/.cache/huggingface/ \
-v ./data:/app/data \
-v ./output:/app/output \
-p 7860:7860 \
-p 8000:8000 \
--shm-size 16G \
--name llama_factory \
-d llama-factory:latest
--name llamafactory \
llamafactory:latest
```
#### 使用 Docker Compose
```bash
docker compose -f ./docker-compose.yml up -d
```
> [!TIP]
> 通过 `docker compose up -d` 使用 Docker Compose 构建镜像。
<details><summary>数据卷详情</summary>

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@ -1,17 +1,23 @@
version: '3.8'
services:
llama-factory:
llamafactory:
build:
dockerfile: Dockerfile
context: .
container_name: llama_factory
args:
INSTALL_BNB: false
INSTALL_VLLM: false
INSTALL_DEEPSPEED: false
PIP_INDEX: https://pypi.org/simple
container_name: llamafactory
volumes:
- ./hf_cache:/root/.cache/huggingface/
- ./data:/app/data
- ./output:/app/output
ports:
- "7860:7860"
- "8000:8000"
ipc: host
deploy:
resources: