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)# 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) - Notebooks
- Google Colab
- Kaggle
File size: 349 Bytes
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{
"idx": 0,
"name": "0",
"path": "",
"type": "sentence_transformers.models.Transformer"
},
{
"idx": 1,
"name": "1",
"path": "1_Pooling",
"type": "sentence_transformers.models.Pooling"
},
{
"idx": 2,
"name": "2",
"path": "2_Normalize",
"type": "sentence_transformers.models.Normalize"
}
] |