fix: docker build failing (#3622)

* fix: uv leftover docs

* fix: docker build failing

* chore: doc

* fix: remove old pytorch build

* fix: stop recommend flash-attn optional, let transformers pull

* fix: remove ring flash attention from image

* fix: quotes [skip ci]

* chore: naming [skip ci]

docs/debugging.qmd

@@ -77,8 +77,9 @@ Make sure you have an [editable install](https://setuptools.pypa.io/en/latest/us
 
 ```bash
 export UV_TORCH_BACKEND=cu128  # or cu130
-uv sync --extra flash-attn --extra deepspeed --group dev --group test
+uv venv --no-project --relocatable
 source .venv/bin/activate
+uv pip install --no-build-isolation -e '.[deepspeed]' --group dev --group test
 ```
 
 #### Remote Hosts
@@ -218,8 +219,9 @@ docker run --privileged --gpus '"all"' --shm-size 10g --rm -it --name axolotl --
 You will now be in the container.  Next, install Axolotl with dev dependencies:
 
 ```bash
-uv sync --extra flash-attn --extra deepspeed --group dev --group test
+uv venv --no-project --relocatable
 source .venv/bin/activate
+uv pip install --no-build-isolation -e '.[deepspeed]' --group dev --group test
 ```
 
 ### Attach To Container

docs/docker.qmd

@@ -13,10 +13,17 @@ This section describes the different Docker images that are released by AxolotlA
 For Blackwell GPUs, please use the tags with PyTorch 2.9.1 and CUDA 12.8.
 :::
 
-::: {.callout-tip}
-Each image below is available in a **uv variant** that uses [uv](https://docs.astral.sh/uv/) with
-a relocatable venv (`/workspace/axolotl-venv`) instead of Miniconda + pip. Append `-uv` to the image name
-(e.g. `axolotlai/axolotl-base-uv`). Tags follow the same format. We recommend the uv images for new deployments.
+::: {.callout-important}
+### Switch to the `-uv` images
+
+Each image below ships a **uv variant** that uses [uv](https://docs.astral.sh/uv/) with a relocatable venv
+(`/workspace/axolotl-venv`) instead of Miniconda + pip. Append `-uv` to the image name
+(e.g. `axolotlai/axolotl-uv`, `axolotlai/axolotl-base-uv`, `axolotlai/axolotl-cloud-uv`). Tags follow the
+same format as their non-uv counterparts.
+
+**We recommend switching to the `-uv` images early.** In the near future we will publish the uv-based
+build to the non-uv tags as well. The non-uv names will continue to work, but they will start serving
+the uv image.
 :::
 
 ## Base
@@ -85,7 +92,7 @@ Tags examples:
 - `main-py3.12-cu130-2.10.0`
 - `main-latest`
 - `main-20260315-py3.11-cu128-2.9.1`
-- `0.12.0`
+- `0.16.1`
 
 ## Cloud
 

docs/faq.qmd

@@ -57,7 +57,7 @@ description: Frequently asked questions
 
 **Q: vLLM is not working with Axolotl**
 
-> A: We currently recommend torch 2.6.0 for use with `vllm`. Please ensure you use the right version. For Docker, please use the `main-py3.11-cu124-2.6.0` tag.
+> A: We currently recommend torch 2.10 for use with `vllm`. Please ensure you use the right version. For Docker, please use the `main-py3.12-cu128-2.10.0` tag (note: torch 2.10 images are built with Python 3.12).
 
 **Q: FA2 2.8.0 `undefined symbol` runtime error on CUDA 12.4**
 

docs/installation.qmd

@@ -15,7 +15,7 @@ This guide covers all the ways you can install and set up Axolotl for your envir
 
 - NVIDIA GPU (Ampere architecture or newer for `bf16` and Flash Attention) or AMD GPU
 - Python ≥3.11
-- PyTorch ≥2.9.0
+- PyTorch ≥2.9.1
 
 ## Installation {#sec-installation}
 
@@ -36,9 +36,9 @@ source $HOME/.local/bin/env
 Choose your CUDA version (e.g. `cu128`, `cu130`), create a venv, and install:
 ```{.bash}
 export UV_TORCH_BACKEND=cu128  # or cu130
-uv venv --no-project --relocatable
+uv venv
 source .venv/bin/activate
-uv pip install --no-build-isolation axolotl[flash-attn,deepspeed]
+uv pip install --no-build-isolation axolotl[deepspeed]
 ```
 
 ### Edge/Development Build {#sec-edge-build}
@@ -49,12 +49,11 @@ For the latest features between releases:
 git clone https://github.com/axolotl-ai-cloud/axolotl.git
 cd axolotl
 export UV_TORCH_BACKEND=cu128  # or cu130
-uv sync --extra flash-attn --extra deepspeed
+uv venv
 source .venv/bin/activate
+uv pip install --no-build-isolation -e '.[deepspeed]'
 ```
 
-`uv sync` creates a `.venv`, installs exact pinned versions from `uv.lock`, and sets up an editable install automatically.
-
 ### Docker {#sec-docker}
 
 ```{.bash}
@@ -132,11 +131,11 @@ source $HOME/.local/bin/env
 
 # Create a fresh venv (recommended for a clean start)
 export UV_TORCH_BACKEND=cu128  # or cu130
-uv venv --no-project --relocatable
+uv venv
 source .venv/bin/activate
 
 # Reinstall axolotl
-uv pip install --no-build-isolation axolotl[flash-attn,deepspeed]
+uv pip install --no-build-isolation axolotl[deepspeed]
 ```
 
 ## Using pip (Alternative) {#sec-pip}
@@ -151,13 +150,13 @@ Follow the instructions at: [https://pytorch.org/get-started/locally/](https://p
 
 ```{.bash}
 pip3 install -U packaging setuptools wheel ninja
-pip3 install --no-build-isolation axolotl[flash-attn,deepspeed]
+pip3 install --no-build-isolation axolotl[deepspeed]
 ```
 
 For editable/development installs:
 ```{.bash}
 pip3 install -U packaging setuptools wheel ninja
-pip3 install --no-build-isolation -e '.[flash-attn,deepspeed]'
+pip3 install --no-build-isolation -e '.[deepspeed]'
 ```
 
 ## Troubleshooting {#sec-troubleshooting}