Feature Extraction
Transformers
Safetensors
French
xlm-roberta
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use OrdalieTech/Solon-embeddings-large-0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OrdalieTech/Solon-embeddings-large-0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="OrdalieTech/Solon-embeddings-large-0.1")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("OrdalieTech/Solon-embeddings-large-0.1") model = AutoModel.from_pretrained("OrdalieTech/Solon-embeddings-large-0.1", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
query :
#7
by YorelNation - opened
Can you show an exemple of what you mean ?
"Instructions :
Add "query : " before the query to retrieve to increase performance of retrieval.
No instructions needed for passages."
When you're embedding your queries, you should embed "query : what are pandas?" instead of just "what are pandas?". The "query : " part is called an instruction, and the passages, i.e. the docs that you're searching for, don't need any instruction.
- Tom Aarsen