Instructions to use BASF-AI/ChEmbed-plug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BASF-AI/ChEmbed-plug with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BASF-AI/ChEmbed-plug", trust_remote_code=True, device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("BASF-AI/ChEmbed-plug", trust_remote_code=True) model = AutoModel.from_pretrained("BASF-AI/ChEmbed-plug", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a99efaa04a3f8741607a122b79898a3357e37042bb6608097b1b0926b4c15cb2
- Size of remote file:
- 547 MB
- SHA256:
- 0230bfd20f625e152dc2fa0c924e63008519aada4c546195699a32ca646606b3
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