medical-1000-64-16-jinaai_jina-embeddings-v2-small-en-10-gpt-4-turbo-0_9062874564 is a fine-tuned version of jinaai/jina-embeddings-v2-small-en designed for a specific domain.
This model is designed to support various applications in natural language processing and understanding.
This the dataset for this model can be found
here.
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:
1from transformers import AutoModel, AutoTokenizer
2
3llm_name = "medical-1000-64-16-jinaai_jina-embeddings-v2-small-en-10-gpt-4-turbo-0_9062874564"
4tokenizer = AutoTokenizer.from_pretrained(llm_name)
5model = AutoModel.from_pretrained(llm_name)
6
7tokens = tokenizer("Your text here", return_tensors="pt")
8embedding = model(**tokens)
