Sentence Similarity
sentence-transformers
PyTorch
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use embaas/sentence-transformers-multilingual-e5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use embaas/sentence-transformers-multilingual-e5-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("embaas/sentence-transformers-multilingual-e5-base") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
Fine tuning in my own domain
#1
by wilfoderek - opened
Guys really amazing work! brave!!!
Now i have a questiosn for all of you. I want to fine tuning this model for my own domain, so could you explain how to achieve this ?
Thanks in advance
Hey,
all credits go to intfloat and Microsoft. @intfloat mentioned his training here: https://github.com/microsoft/unilm/tree/master/simlm.
But the model you work also with sentence-transformers training functions.
Another possibility would be just to fine tune the last layer, which seems to be a easy and powerful solution. Check out this here.
Man, thank you so much! i will check out "Another possibility would be just to fine tune the last layer". i
Banso changed discussion status to closed