florian-hoenicke's picture
feat: push custom model
00c615e verified
metadata
license: apache-2.0
datasets:
  - fine-tuned/arguana-c-256-24-gpt-4o-2024-05-13-51550
  - allenai/c4
language:
  - en
pipeline_tag: feature-extraction
tags:
  - sentence-transformers
  - feature-extraction
  - sentence-similarity
  - mteb
  - Argumentation
  - Corpus
  - Research
  - Quality
  - Dataset

This model is a fine-tuned version of jinaai/jina-embeddings-v2-base-en designed for the following use case:

academic research data retrieval

How to Use

This model can be easily integrated into your NLP pipeline for tasks such as text classification, sentiment analysis, entity recognition, and more. Here's a simple example to get you started:

from sentence_transformers import SentenceTransformer
from sentence_transformers.util import cos_sim

model = SentenceTransformer(
    'fine-tuned/arguana-c-256-24-gpt-4o-2024-05-13-51550',
    trust_remote_code=True
)

embeddings = model.encode([
    'first text to embed',
    'second text to embed'
])
print(cos_sim(embeddings[0], embeddings[1]))