Instructions to use iamroot/zero-shot-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iamroot/zero-shot-embedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="iamroot/zero-shot-embedding", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("iamroot/zero-shot-embedding", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 379 Bytes
def591b f64bef6 def591b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"architectures": [
"ZeroShotEmbedding"
],
"auto_map": {
"AutoConfig": "model.ZeroShotEmbeddingConfig",
"AutoModel": "model.ZeroShotEmbedding"
},
"base_embedding_model": "all-mpnet-base-v2",
"hidden_size": 2048,
"input_size": 768,
"model_type": "embedding-head",
"output_size": 128,
"torch_dtype": "float32",
"transformers_version": "4.35.1"
}
|