|
--- |
|
license: other |
|
language: |
|
- en |
|
library_name: diffusers |
|
--- |
|
# FLUX.1-merged |
|
|
|
This repository provides the merged params for [`black-forest-labs/FLUX.1-dev`](https://huggingface.co/black-forest-labs/FLUX.1-dev) |
|
and [`black-forest-labs/FLUX.1-schnell`](https://huggingface.co/black-forest-labs/FLUX.1-schnell). Please be aware of the licenses of both |
|
the models before using the params commercially. |
|
|
|
<table> |
|
<thead> |
|
<tr> |
|
<th>Dev (50 steps)</th> |
|
<th>Dev (4 steps)</th> |
|
<th>Dev + Schnell (4 steps)</th> |
|
</tr> |
|
</thead> |
|
<tbody> |
|
<tr> |
|
<td> |
|
<img src="./assets/flux.png" alt="Dev 50 Steps"> |
|
</td> |
|
<td> |
|
<img src="./assets/flux_4.png" alt="Dev 4 Steps"> |
|
</td> |
|
<td> |
|
<img src="./assets/merged_flux.png" alt="Dev + Schnell 4 Steps"> |
|
</td> |
|
</tr> |
|
</tbody> |
|
</table> |
|
|
|
## Sub-memory-efficient merging code |
|
|
|
```python |
|
from diffusers import FluxTransformer2DModel |
|
from huggingface_hub import snapshot_download |
|
from accelerate import init_empty_weights |
|
from diffusers.models.model_loading_utils import load_model_dict_into_meta |
|
import safetensors.torch |
|
import glob |
|
import torch |
|
|
|
|
|
with init_empty_weights(): |
|
config = FluxTransformer2DModel.load_config("black-forest-labs/FLUX.1-dev", subfolder="transformer") |
|
model = FluxTransformer2DModel.from_config(config) |
|
|
|
dev_ckpt = snapshot_download(repo_id="black-forest-labs/FLUX.1-dev", allow_patterns="transformer/*") |
|
schnell_ckpt = snapshot_download(repo_id="black-forest-labs/FLUX.1-schnell", allow_patterns="transformer/*") |
|
|
|
dev_shards = sorted(glob.glob(f"{dev_ckpt}/transformer/*.safetensors")) |
|
schnell_shards = sorted(glob.glob(f"{schnell_ckpt}/transformer/*.safetensors")) |
|
|
|
merged_state_dict = {} |
|
guidance_state_dict = {} |
|
|
|
for i in range(len((dev_shards))): |
|
state_dict_dev_temp = safetensors.torch.load_file(dev_shards[i]) |
|
state_dict_schnell_temp = safetensors.torch.load_file(schnell_shards[i]) |
|
|
|
keys = list(state_dict_dev_temp.keys()) |
|
for k in keys: |
|
if "guidance" not in k: |
|
merged_state_dict[k] = (state_dict_dev_temp.pop(k) + state_dict_schnell_temp.pop(k)) / 2 |
|
else: |
|
guidance_state_dict[k] = state_dict_dev_temp.pop(k) |
|
|
|
if len(state_dict_dev_temp) > 0: |
|
raise ValueError(f"There should not be any residue but got: {list(state_dict_dev_temp.keys())}.") |
|
if len(state_dict_schnell_temp) > 0: |
|
raise ValueError(f"There should not be any residue but got: {list(state_dict_dev_temp.keys())}.") |
|
|
|
merged_state_dict.update(guidance_state_dict) |
|
load_model_dict_into_meta(model, merged_state_dict) |
|
|
|
model.to(torch.bfloat16).save_pretrained("/raid/.cache/huggingface/merged-flux") |
|
``` |
|
|
|
## Inference code |
|
|
|
```python |
|
from diffusers import FluxPipeline, FluxTransformer2DModel |
|
import torch |
|
|
|
transformer = FluxTransformer2DModel.from_pretrained("sayakpaul/FLUX.1-merged", torch_dtype=torch.bfloat16) |
|
pipeline = FluxPipeline.from_pretrained( |
|
"black-forest-labs/FLUX.1-dev", transformer=transformer, torch_dtype=torch.bfloat16 |
|
).to("cuda") |
|
image = pipeline( |
|
prompt="a tiny astronaut hatching from an egg on the moon", |
|
guidance_scale=3.5, |
|
num_inference_steps=50, |
|
height=880, |
|
width=1184, |
|
max_sequence_length=512, |
|
generator=torch.manual_seed(0), |
|
).images[0] |
|
image.save("merged_flux.png") |
|
``` |
|
|
|
## Documentation |
|
|
|
* https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux |
|
* https://huggingface.co/docs/diffusers/main/en/api/models/flux_transformer |
