Feature Extraction
Transformers
Safetensors
Thai
English
clip_text_camembert
openthaigpt
custom_code
Instructions to use openthaigpt/CLIPTextCamembertModelWithProjection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openthaigpt/CLIPTextCamembertModelWithProjection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="openthaigpt/CLIPTextCamembertModelWithProjection", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openthaigpt/CLIPTextCamembertModelWithProjection", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4faedbc97b8b9d2a6dfe3a6664a83fd95167b93b9663cd7f295fe4388d8a697
- Size of remote file:
- 423 MB
- SHA256:
- 827e46c81eff27861cd95815354c6b5b62585133e93b2761258d9d6db81d0f97
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