Instructions to use Abdullah707/Stable-Text-Encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abdullah707/Stable-Text-Encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Abdullah707/Stable-Text-Encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Abdullah707/Stable-Text-Encoder") model = AutoModel.from_pretrained("Abdullah707/Stable-Text-Encoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d46f1f18c42a77832d73244cfd40c33237dbaf1009c6652d5180219f20f12165
- Size of remote file:
- 246 MB
- SHA256:
- 05eee911f195625deeab86f0b22b115d7d8bc3adbfc1404f03557f7e4e6a8fd7
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