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README: simplify AI model offline download — remove iptables option

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Replace two-option (iptables vs download) with a single clear offline
download path using huggingface-cli into ./data/hf_cache.

https://claude.ai/code/session_01WVDg7amsy1TTtxvpku7bcM
This commit is contained in:
Claude
2026-06-14 00:38:45 +00:00
parent 11772e620c
commit b63a4f9187
1 changed files with 13 additions and 12 deletions
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README.md
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@@ -208,32 +208,33 @@ docker compose -f docker-compose.gpu.yml logs | grep -i sam
If Docker created `./data/` as root and you can't write there without `sudo`, you can also use root's curl as above — the container reads the file regardless of owner. If Docker created `./data/` as root and you can't write there without `sudo`, you can also use root's curl as above — the container reads the file regardless of owner.
**AI Edit returns "model files not yet downloaded" or "Errno -3 / DNS" error** **AI models not downloading (container DNS blocked)**
The container's DNS is blocked (common on corporate networks or custom iptables rules), so it can't download SDXL models from HuggingFace. Two options: If the container can't reach HuggingFace (`Errno -3` in logs), download the model files directly on the host — no rebuild needed, the container reads from the same `./data/hf_cache/` folder.
*Option A — fix Docker DNS (recommended, one command):*
```bash
sudo iptables -I DOCKER-USER -p udp --dport 53 -j ACCEPT
docker compose -f docker-compose.gpu.yml restart
```
*Option B — pre-download models on the host (if iptables fix isn't possible):*
```bash ```bash
pip install huggingface-hub pip install huggingface-hub
# Download the inpainting model (~6.5 GB, needed for AI Edit): # Inpainting model (~6.5 GB) — needed for AI Edit, Make less symmetrical, etc.
huggingface-cli download diffusers/stable-diffusion-xl-1.0-inpainting-0.1 \ huggingface-cli download diffusers/stable-diffusion-xl-1.0-inpainting-0.1 \
--cache-dir ./data/hf_cache \ --cache-dir ./data/hf_cache \
--exclude "*.msgpack" "flax_*" "tf_*" --exclude "*.msgpack" "flax_*" "tf_*"
# Download the text-to-image model (~6.5 GB, needed for Text → Image): # Text-to-image model (~6.5 GB) — needed for Text → Image
huggingface-cli download stabilityai/stable-diffusion-xl-base-1.0 \ huggingface-cli download stabilityai/stable-diffusion-xl-base-1.0 \
--cache-dir ./data/hf_cache \ --cache-dir ./data/hf_cache \
--exclude "*.msgpack" "flax_*" "tf_*" --exclude "*.msgpack" "flax_*" "tf_*"
``` ```
The models land in `./data/hf_cache/` which is bind-mounted into the container — no rebuild needed. Restart the container and the first AI Edit request loads from local disk. Once both downloads finish, restart the container:
```bash
docker compose -f docker-compose.gpu.yml restart
```
The first AI Edit request loads from local disk (10–30 s, not a download). Verify in logs:
```bash
docker compose -f docker-compose.gpu.yml logs -f | grep -E "local_gpu|Cached|failed"
```
**Out of VRAM during generation** **Out of VRAM during generation**
- Reduce `LOCAL_GPU_MAX_PIPELINES=1` in `.env` (default 2) - Reduce `LOCAL_GPU_MAX_PIPELINES=1` in `.env` (default 2)