Instructions to use hkunlp/instructor-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hkunlp/instructor-xl with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hkunlp/instructor-xl") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use hkunlp/instructor-xl with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hkunlp/instructor-xl") model = AutoModel.from_pretrained("hkunlp/instructor-xl") - Notebooks
- Google Colab
- Kaggle
multilingual support?
Hi,
Excellent sota model! Does the model support other languages besides english?
Hi, Thanks a lot for your interests in the INSTRUCTOR model!
As the INSTRUCTOR model is only trained on English texts, it may not support multilingual settings for now.
Hi, Thanks a lot for your interests in the INSTRUCTOR model!
As the INSTRUCTOR model is only trained on English texts, it may not support multilingual settings for now.
thanks!
This model is excellent.
Is there any comparable model for embeddings that (also) covers the German language?
What would be the process to train in another language?
- Translate the data training from english to required lenguage.
The rest of the steps are unkown for me. Any idea?
Thank you for this, it is very thoughtful and useful.
But, any support for multiple languages yet? I can support in any way that's possible :)