Card: show loading the published converted weights via dit_repo
Browse files
README.md
CHANGED
|
@@ -23,10 +23,10 @@ denoise trajectory, so quantized samples differ in composition from bf16 but are
|
|
| 23 |
## Usage
|
| 24 |
|
| 25 |
```python
|
| 26 |
-
import mlx.core as mx
|
| 27 |
from lens_mlx.pipeline_mlx import LensPipeline # github.com/xocialize-code/lens-mlx
|
| 28 |
|
| 29 |
-
|
|
|
|
| 30 |
img = pipe("A serene lake below snow-capped mountains, golden hour.",
|
| 31 |
height=1024, width=1024, num_inference_steps=20, seed=42)
|
| 32 |
img.save("out.png")
|
|
|
|
| 23 |
## Usage
|
| 24 |
|
| 25 |
```python
|
|
|
|
| 26 |
from lens_mlx.pipeline_mlx import LensPipeline # github.com/xocialize-code/lens-mlx
|
| 27 |
|
| 28 |
+
# `base` = a microsoft/Lens snapshot providing the tokenizer, GPT-OSS encoder, and FLUX.2 VAE.
|
| 29 |
+
pipe = LensPipeline.from_pretrained(base, dit_repo="mlx-community/Lens-3.8B-4bit")
|
| 30 |
img = pipe("A serene lake below snow-capped mountains, golden hour.",
|
| 31 |
height=1024, width=1024, num_inference_steps=20, seed=42)
|
| 32 |
img.save("out.png")
|