| # medical-20-0-16-jinaai_jina-embeddings-v2-small-en-1000-gpt-4-turbo-01_9062874564 | |
| ## Model Description | |
| medical-20-0-16-jinaai_jina-embeddings-v2-small-en-1000-gpt-4-turbo-01_9062874564 is a fine-tuned version of jinaai/jina-embeddings-v2-small-en designed for a specific domain. | |
| ## Use Case | |
| This model is designed to support various applications in natural language processing and understanding. | |
| ## Associated Dataset | |
| This the dataset for this model can be found [**here**](https://huggingface.co/datasets/florianhoenicke/medical-20-0-16-jinaai_jina-embeddings-v2-small-en-1000-gpt-4-turbo-01_9062874564). | |
| ## 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: | |
| ```python | |
| from transformers import AutoModel, AutoTokenizer | |
| llm_name = "medical-20-0-16-jinaai_jina-embeddings-v2-small-en-1000-gpt-4-turbo-01_9062874564" | |
| tokenizer = AutoTokenizer.from_pretrained(llm_name) | |
| model = AutoModel.from_pretrained(llm_name) | |
| tokens = tokenizer("Your text here", return_tensors="pt") | |
| embedding = model(**tokens) | |
| ``` | |