Video Classification
Transformers
PyTorch
Safetensors
English
xclip
feature-extraction
vision
Eval Results (legacy)
Instructions to use microsoft/xclip-large-patch14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/xclip-large-patch14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="microsoft/xclip-large-patch14")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("microsoft/xclip-large-patch14") model = AutoModelForMultimodalLM.from_pretrained("microsoft/xclip-large-patch14") - Notebooks
- Google Colab
- Kaggle
怎么使用
#1
by xxiani - opened
- .gitattributes +0 -1
- model.safetensors +0 -3
.gitattributes
CHANGED
|
@@ -30,4 +30,3 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 30 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 31 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 32 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 33 |
-
model.safetensors filter=lfs diff=lfs merge=lfs -text
|
|
|
|
| 30 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 31 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 32 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
model.safetensors
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:5dfd16f191d773419419419b3ed4f4b72c20923347b0265373bd733fd69f7332
|
| 3 |
-
size 2302811148
|
|
|
|
|
|
|
|
|
|
|
|