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OpenDAS
diffusers
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045157a4
Unverified
Commit
045157a4
authored
Nov 10, 2022
by
Pedro Cuenca
Committed by
GitHub
Nov 10, 2022
Browse files
Fix Flax usage comments (#1211)
* Fix Flax usage comments (they didn't work). * Spell out dtype * make style
parent
a09d4753
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src/diffusers/pipeline_flax_utils.py
src/diffusers/pipeline_flax_utils.py
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src/diffusers/pipeline_flax_utils.py
View file @
045157a4
...
@@ -268,18 +268,27 @@ class FlaxDiffusionPipeline(ConfigMixin):
...
@@ -268,18 +268,27 @@ class FlaxDiffusionPipeline(ConfigMixin):
>>> from diffusers import FlaxDiffusionPipeline
>>> from diffusers import FlaxDiffusionPipeline
>>> # Download pipeline from huggingface.co and cache.
>>> # Download pipeline from huggingface.co and cache.
>>> pipeline = FlaxDiffusionPipeline.from_pretrained("CompVis/ldm-text2im-large-256")
>>> # Requires to be logged in to Hugging Face hub,
>>> # see more in [the documentation](https://huggingface.co/docs/hub/security-tokens)
>>> # Download pipeline that requires an authorization token
>>> pipeline, params = FlaxDiffusionPipeline.from_pretrained(
>>> # For more information on access tokens, please refer to this section
... "runwayml/stable-diffusion-v1-5",
>>> # of the documentation](https://huggingface.co/docs/hub/security-tokens)
... revision="bf16",
>>> pipeline = FlaxDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
... dtype=jnp.bfloat16,
... )
>>> # Download pipeline, but overwrite scheduler
>>> from diffusers import LMSDiscreteScheduler
>>> # Download pipeline, but use a different scheduler
>>> from diffusers import FlaxDPMSolverMultistepScheduler
>>> scheduler = LMSDiscreteScheduler.from_config("runwayml/stable-diffusion-v1-5", subfolder="scheduler")
>>> pipeline = FlaxDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", scheduler=scheduler)
>>> model_id = "runwayml/stable-diffusion-v1-5"
>>> sched, sched_state = FlaxDPMSolverMultistepScheduler.from_config(
... model_id,
... subfolder="scheduler",
... )
>>> dpm_pipe, dpm_params = FlaxStableDiffusionPipeline.from_pretrained(
... model_id, revision="bf16", dtype=jnp.bfloat16, scheduler=dpmpp
... )
>>> dpm_params["scheduler"] = dpmpp_state
```
```
"""
"""
cache_dir
=
kwargs
.
pop
(
"cache_dir"
,
DIFFUSERS_CACHE
)
cache_dir
=
kwargs
.
pop
(
"cache_dir"
,
DIFFUSERS_CACHE
)
...
...
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