Instructions to use LanguageBind/LanguageBind_Thermal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LanguageBind/LanguageBind_Thermal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="LanguageBind/LanguageBind_Thermal") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoModelForZeroShotImageClassification model = AutoModelForZeroShotImageClassification.from_pretrained("LanguageBind/LanguageBind_Thermal", dtype="auto") - Notebooks
- Google Colab
- Kaggle
linbin commited on
Commit ·
e7fdfbe
1
Parent(s): d1a4cec
Upload config.json
Browse files- config.json +1 -1
config.json
CHANGED
|
@@ -5,7 +5,7 @@
|
|
| 5 |
],
|
| 6 |
"initializer_factor": 1.0,
|
| 7 |
"logit_scale_init_value": 2.6592,
|
| 8 |
-
"model_type": "
|
| 9 |
"projection_dim": 768,
|
| 10 |
"text_config": {
|
| 11 |
"_name_or_path": "",
|
|
|
|
| 5 |
],
|
| 6 |
"initializer_factor": 1.0,
|
| 7 |
"logit_scale_init_value": 2.6592,
|
| 8 |
+
"model_type": "LanguageBindThermal",
|
| 9 |
"projection_dim": 768,
|
| 10 |
"text_config": {
|
| 11 |
"_name_or_path": "",
|