Feature Extraction
Transformers
Safetensors
bert
tevatron
tevatron-elastic
information-retrieval
retriever
elastic
text-embeddings-inference
Instructions to use utahnlp/tevatron-elastic-bert-retriever-mrl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use utahnlp/tevatron-elastic-bert-retriever-mrl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="utahnlp/tevatron-elastic-bert-retriever-mrl")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("utahnlp/tevatron-elastic-bert-retriever-mrl") model = AutoModel.from_pretrained("utahnlp/tevatron-elastic-bert-retriever-mrl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "pooling": "cls", | |
| "normalize": true, | |
| "points": [ | |
| { | |
| "layer": 12, | |
| "dim": 32, | |
| "name": null | |
| }, | |
| { | |
| "layer": 12, | |
| "dim": 64, | |
| "name": null | |
| }, | |
| { | |
| "layer": 12, | |
| "dim": 128, | |
| "name": null | |
| }, | |
| { | |
| "layer": 12, | |
| "dim": 256, | |
| "name": null | |
| }, | |
| { | |
| "layer": 12, | |
| "dim": 512, | |
| "name": null | |
| }, | |
| { | |
| "layer": 12, | |
| "dim": 768, | |
| "name": null | |
| } | |
| ] | |
| } |