tocmo0nlord/axolotl
1
0
Fork 0
Code Issues Pull Requests Actions 2 Packages Projects Releases Wiki Activity

Built site for gh-pages

Browse Source
This commit is contained in:
Quarto GHA Workflow Runner
2024-07-11 13:20:35 +00:00
parent d2a96e9b1d
commit 5ad84a9488
26 changed files with 70 additions and 70 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
search.json
View File

@@ -48,7 +48,7 @@
"href": "docs/debugging.html#debugging-with-docker",
"title": "Debugging",
"section": "Debugging With Docker",
"text": "Debugging With Docker\nUsing official Axolotl Docker images is a great way to debug your code, and is a very popular way to use Axolotl. Attaching VSCode to Docker takes a few more steps.\n\nSetup\nOn the host that is running axolotl (ex: if you are using a remote host), clone the axolotl repo and change your current directory to the root:\ngit clone https://github.com/OpenAccess-AI-Collective/axolotl\ncd axolotl\n\n[!Tip] If you already have axolotl cloned on your host, make sure you have the latest changes and change into the root of the project.\n\nNext, run the desired docker image and mount the current directory. Below is a docker command you can run to do this:2\ndocker run --privileged --gpus '\"all\"' --shm-size 10g --rm -it --name axolotl --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 --mount type=bind,src=\"${PWD}\",target=/workspace/axolotl -v ${HOME}/.cache/huggingface:/root/.cache/huggingface winglian/axolotl:main-py3.10-cu118-2.0.1\n\n[!Tip] To understand which containers are available, see the Docker section of the README and the DockerHub repo. For details of how the Docker containers are built, see axolotl’s Docker CI builds.\n\nYou will now be in the container. Next, perform an editable install of Axolotl:\npip3 install packaging\npip3 install -e '.[flash-attn,deepspeed]'\n\n\nAttach To Container\nNext, if you are using a remote host, Remote into this host with VSCode. If you are using a local host, you can skip this step.\nNext, select Dev Containers: Attach to Running Container... using the command palette (CMD + SHIFT + P) in VSCode. You will be prompted to select a container to attach to. Select the container you just created. You will now be in the container with a working directory that is at the root of the project. Any changes you make to the code will be reflected both in the container and on the host.\nNow you are ready to debug as described above (see Debugging with VSCode).\n\n\nVideo - Attaching To Docker On Remote Host\nHere is a short video that demonstrates how to attach to a Docker container on a remote host:\n\n\n\nHamel Husain’s tutorial: Debugging Axolotl Part 2: Attaching to Docker on a Remote Host",
"text": "Debugging With Docker\nUsing official Axolotl Docker images is a great way to debug your code, and is a very popular way to use Axolotl. Attaching VSCode to Docker takes a few more steps.\n\nSetup\nOn the host that is running axolotl (ex: if you are using a remote host), clone the axolotl repo and change your current directory to the root:\ngit clone https://github.com/axolotl-ai-cloud/axolotl\ncd axolotl\n\n[!Tip] If you already have axolotl cloned on your host, make sure you have the latest changes and change into the root of the project.\n\nNext, run the desired docker image and mount the current directory. Below is a docker command you can run to do this:2\ndocker run --privileged --gpus '\"all\"' --shm-size 10g --rm -it --name axolotl --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 --mount type=bind,src=\"${PWD}\",target=/workspace/axolotl -v ${HOME}/.cache/huggingface:/root/.cache/huggingface winglian/axolotl:main-py3.10-cu118-2.0.1\n\n[!Tip] To understand which containers are available, see the Docker section of the README and the DockerHub repo. For details of how the Docker containers are built, see axolotl’s Docker CI builds.\n\nYou will now be in the container. Next, perform an editable install of Axolotl:\npip3 install packaging\npip3 install -e '.[flash-attn,deepspeed]'\n\n\nAttach To Container\nNext, if you are using a remote host, Remote into this host with VSCode. If you are using a local host, you can skip this step.\nNext, select Dev Containers: Attach to Running Container... using the command palette (CMD + SHIFT + P) in VSCode. You will be prompted to select a container to attach to. Select the container you just created. You will now be in the container with a working directory that is at the root of the project. Any changes you make to the code will be reflected both in the container and on the host.\nNow you are ready to debug as described above (see Debugging with VSCode).\n\n\nVideo - Attaching To Docker On Remote Host\nHere is a short video that demonstrates how to attach to a Docker container on a remote host:\n\n\n\nHamel Husain’s tutorial: Debugging Axolotl Part 2: Attaching to Docker on a Remote Host",
"crumbs": [
"How-To Guides",
"Debugging"
@@ -404,7 +404,7 @@
"href": "index.html#quickstart",
"title": "Axolotl",
"section": "Quickstart ⚡",
"text": "Quickstart ⚡\nGet started with Axolotl in just a few steps! This quickstart guide will walk you through setting up and running a basic fine-tuning task.\nRequirements: Python >=3.10 and Pytorch >=2.1.1.\ngit clone https://github.com/OpenAccess-AI-Collective/axolotl\ncd axolotl\n\npip3 install packaging ninja\npip3 install -e '.[flash-attn,deepspeed]'\n\nUsage\n# preprocess datasets - optional but recommended\nCUDA_VISIBLE_DEVICES=\"\" python -m axolotl.cli.preprocess examples/openllama-3b/lora.yml\n\n# finetune lora\naccelerate launch -m axolotl.cli.train examples/openllama-3b/lora.yml\n\n# inference\naccelerate launch -m axolotl.cli.inference examples/openllama-3b/lora.yml \\\n --lora_model_dir=\"./outputs/lora-out\"\n\n# gradio\naccelerate launch -m axolotl.cli.inference examples/openllama-3b/lora.yml \\\n --lora_model_dir=\"./outputs/lora-out\" --gradio\n\n# remote yaml files - the yaml config can be hosted on a public URL\n# Note: the yaml config must directly link to the **raw** yaml\naccelerate launch -m axolotl.cli.train https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/examples/openllama-3b/lora.yml",
"text": "Quickstart ⚡\nGet started with Axolotl in just a few steps! This quickstart guide will walk you through setting up and running a basic fine-tuning task.\nRequirements: Python >=3.10 and Pytorch >=2.1.1.\ngit clone https://github.com/axolotl-ai-cloud/axolotl\ncd axolotl\n\npip3 install packaging ninja\npip3 install -e '.[flash-attn,deepspeed]'\n\nUsage\n# preprocess datasets - optional but recommended\nCUDA_VISIBLE_DEVICES=\"\" python -m axolotl.cli.preprocess examples/openllama-3b/lora.yml\n\n# finetune lora\naccelerate launch -m axolotl.cli.train examples/openllama-3b/lora.yml\n\n# inference\naccelerate launch -m axolotl.cli.inference examples/openllama-3b/lora.yml \\\n --lora_model_dir=\"./outputs/lora-out\"\n\n# gradio\naccelerate launch -m axolotl.cli.inference examples/openllama-3b/lora.yml \\\n --lora_model_dir=\"./outputs/lora-out\" --gradio\n\n# remote yaml files - the yaml config can be hosted on a public URL\n# Note: the yaml config must directly link to the **raw** yaml\naccelerate launch -m axolotl.cli.train https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/examples/openllama-3b/lora.yml",
"crumbs": [
"Home"
]
@@ -454,7 +454,7 @@
"href": "index.html#badge",
"title": "Axolotl",
"section": "Badge ❤🏷️",
"text": "Badge ❤🏷️\nBuilding something cool with Axolotl? Consider adding a badge to your model card.\n[<img src=\"https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png\" alt=\"Built with Axolotl\" width=\"200\" height=\"32\"/>](https://github.com/OpenAccess-AI-Collective/axolotl)",
"text": "Badge ❤🏷️\nBuilding something cool with Axolotl? Consider adding a badge to your model card.\n[<img src=\"https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png\" alt=\"Built with Axolotl\" width=\"200\" height=\"32\"/>](https://github.com/axolotl-ai-cloud/axolotl)",
"crumbs": [
"Home"
]
@@ -501,7 +501,7 @@
"href": "examples/colab-notebooks/colab-axolotl-example.html#install-axolotl-and-dependencies",
"title": "Example notebook for running Axolotl on google colab",
"section": "Install Axolotl and dependencies",
"text": "Install Axolotl and dependencies\n\n!pip install torch==\"2.1.2\"\n!pip install -e git+https://github.com/OpenAccess-AI-Collective/axolotl#egg=axolotl\n!pip install flash-attn==\"2.5.0\"\n!pip install deepspeed==\"0.13.1\"!pip install mlflow==\"2.13.0\""
"text": "Install Axolotl and dependencies\n\n!pip install torch==\"2.1.2\"\n!pip install -e git+https://github.com/axolotl-ai-cloud/axolotl#egg=axolotl\n!pip install flash-attn==\"2.5.0\"\n!pip install deepspeed==\"0.13.1\"!pip install mlflow==\"2.13.0\""
},
{
"objectID": "examples/colab-notebooks/colab-axolotl-example.html#create-an-yaml-config-file",