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https://github.com/splittydev/flux1-cli
Easy local FLUX.1 Inference
https://github.com/splittydev/flux1-cli
bfl cli flux1 flux1ai generative-ai inference lora
Last synced: 2 months ago
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Easy local FLUX.1 Inference
- Host: GitHub
- URL: https://github.com/splittydev/flux1-cli
- Owner: SplittyDev
- License: mit
- Created: 2024-08-20T05:45:35.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2024-08-29T18:27:42.000Z (4 months ago)
- Last Synced: 2024-08-29T20:47:00.621Z (4 months ago)
- Topics: bfl, cli, flux1, flux1ai, generative-ai, inference, lora
- Language: Python
- Homepage:
- Size: 412 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# FLUX.1 Inference CLI
> Supports MPS (Apple Silicon), CUDA and CPU
## Features
- **Multiple Models**: Supports FLUX.1-schnell and FLUX.1-dev
- **LoRA Support**: Interactive LoRA picker for easy selection
- **Cross-Platform**: Supports MPS, CUDA and CPU
- **Tested on macOS**: Works well on Apple Silicon[^1]
## Installation
**Cloning the repository**:
```bash
git clone https://github.com/SplittyDev/flux1-cli.git
cd flux1-cli
```
**Using uv (recommended)**:
```bash
uv venv
source .venv/bin/activate
uv pip install -r requirements.txt
python3 src/main.py
```
**Using pip**:
```bash
python3 -m venv .venv
source .venv/bin/activate
python3 -m pip install -r requirements.txt
python3 src/main.py
```
### Installing LoRAs
Simply put your `.safetensors` files in the `lora` directory.
They will be available immediately when typing `/lora`.
## Prompting
### Inference Modifiers
The CLI supports various modifiers, which can be added to the end of the prompt, like this:
- `Photograph of a meadow in a forest /fast`
- `Photograph of a meadow in a forest /1024x768 /slow`
- `Photograph of a meadow in a forest /seed=1234 /8`
**List of Modifiers**:
| Modifier | Description |
|--------------------|------------------------------------------------------------|
| `/f`, `/fast` | Use a small number of inference steps for fast results |
| `/s`, `/slow` | Use a large number of inference steps for accurate results |
| `/a`, `/again` | Reuse the previous seed for the next inference |
| `/r`, `/random` | Use a random seed for the next inference |
| `/` if n < 128 | Use this number of inference steps for the next inference |
| `/` if n >= 128 | Set the resolution to `nxn` |
| `/x` | Set the resolution to `wxh` |
### Standalone Modifiers
The CLI also supports standalone modifiers, which only work on their own line.
**List of Standalone Modifiers**:
| Modifier | Description |
|-----------------------|-------------------------------|
| `/quit` | Quit the CLI |
| `/lora` | Show LoRA picker |
| `/lora_scale=` | Set the LoRA scale to `scale` |
| `/seed=` | Set the seed to `seed` |
### Tips and Tricks
- Leaving the prompt completely empty will repeat the last prompt
- You can combine modifiers, like this: `Photograph of a meadow in a forest /fast /seed=1234`
- You can apply new modifiers without repeating the prompt, like this: `/slow /1024x768`
- Images are saved in this format: `output//_.png`
### Example workflows with modifiers
**Annotated example, explaning the thought process**
```ini
# Initial prompt. Generate images fast, to get a feeling for the prompt.
λ Prompt: Photograph of a meadow in a forest /fast
# Refine prompt. Fast mode is still active, no need to repeat it.
λ Prompt: High resolution photograph of a meadow in a forest
# This looks nice! Let's generate the same image again, but in slow mode.
λ Prompt: /again /slow
# Let's keep the same prompt, but randomize the seed again.
λ Prompt: /random
# Let's try it in landscape mode, but fast, to see if it looks better.
λ Prompt: /1920x1080 /fast
# Alright, let's call it a day
λ Prompt: /quit
```
**Real-world example, using shortcuts and no comments**
```ini
λ Prompt: Photograph of a moonlit meadow in a mythical forest/f
λ Prompt:
λ Prompt: /a/s
λ Prompt: Stunning photograph of a moonlit meadow in a mythical forest, godrays/r/f
λ Prompt: /a/s
λ Prompt: /quit
```
## Troubleshooting
**I don't have enough VRAM**:
> You can pass the `--offload-cpu` flag to offload parts of the model to the CPU for lower VRAM usage with a small performance hit. Sadly this doesn't seem to work with MPS. If anyone knows why, please let me know!
**I wanna use the CPU (for whatever reason)**:
> You can pass the `--force-cpu` flag to force CPU inference. This is not recommended, as it's _much_ slower than MPS or CUDA.
**High resolution images are broken**
> FLUX.1 has a maximum resolution of 2MP. These are _roughly_ the largest possible sizes[^2]:
> - 1:1 exact 1448 x 1448, rounded 1408 x 1408
> - 3:2 exact 1773 x 1182, rounded 1728 x 1152
> - 4:3 exact 1672 x 1254, rounded 1664 x 1216
> - 16:9 exact 1936 x 1089, rounded 1920 x 1088
> - 21:9 exact 2212 x 948, rounded 2176 x 960
>
> You can use an upscaler (not included) to increase the resolution.
[^1]: Tested on 2023 Mac Studio, 128GB Unified RAM, 24-Core Apple M2 Ultra
[^2]: See [this post on Reddit](https://www.reddit.com/r/StableDiffusion/comments/1enxdga/flux_recommended_resolutions_from_01_to_20/). Thanks `u/Aplakka`!