Instructions to use sthui/SimpleSeg-Kimi-VL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sthui/SimpleSeg-Kimi-VL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sthui/SimpleSeg-Kimi-VL", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sthui/SimpleSeg-Kimi-VL", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
songtianhui commited on
Commit ·
bcbe017
1
Parent(s): 1d08b80
update
Browse files
README.md
CHANGED
|
@@ -87,7 +87,7 @@ It is recommended to use python=3.10, torch>=2.1.0, and transformers=4.48.2 as t
|
|
| 87 |
```python
|
| 88 |
from PIL import Image
|
| 89 |
from transformers import AutoModelForCausalLM, AutoProcessor
|
| 90 |
-
model_path = "
|
| 91 |
model = AutoModelForCausalLM.from_pretrained(
|
| 92 |
model_path,
|
| 93 |
torch_dtype="auto",
|
|
|
|
| 87 |
```python
|
| 88 |
from PIL import Image
|
| 89 |
from transformers import AutoModelForCausalLM, AutoProcessor
|
| 90 |
+
model_path = "sthui/SimpleSeg-Kimi-VL"
|
| 91 |
model = AutoModelForCausalLM.from_pretrained(
|
| 92 |
model_path,
|
| 93 |
torch_dtype="auto",
|