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:
- d4671d879e5e34b1cf891e53a667f3c257fd783e596c5a2e9f57019307354093
- Size of remote file:
- 492 MB
- SHA256:
- 770a47a9ffdcfda0b05506a7888ed714d06131d60267e6cf52765d61cf59fd67
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