Instructions to use baidu/ERNIE-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use baidu/ERNIE-Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("baidu/ERNIE-Image", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update pe_tokenizer/tokenizer_config.json
Browse files
pe_tokenizer/tokenizer_config.json
CHANGED
|
@@ -1005,7 +1005,7 @@
|
|
| 1005 |
"<SPECIAL_999>"
|
| 1006 |
],
|
| 1007 |
"is_local": true,
|
| 1008 |
-
"model_max_length":
|
| 1009 |
"pad_token": "<pad>",
|
| 1010 |
"processor_class": "PixtralProcessor",
|
| 1011 |
"tokenizer_class": "TokenizersBackend",
|
|
|
|
| 1005 |
"<SPECIAL_999>"
|
| 1006 |
],
|
| 1007 |
"is_local": true,
|
| 1008 |
+
"model_max_length": 2048,
|
| 1009 |
"pad_token": "<pad>",
|
| 1010 |
"processor_class": "PixtralProcessor",
|
| 1011 |
"tokenizer_class": "TokenizersBackend",
|