| # fine-tuned/medical-10-10-1-jinaai_jina-embeddings-v2-small-en-50-gpt-3.5-turbo-01_8647177611 | |
| ## Model Description | |
| fine-tuned/medical-10-10-1-jinaai_jina-embeddings-v2-small-en-50-gpt-3.5-turbo-01_8647177611 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/fine-tuned/fine-tuned/medical-10-10-1-jinaai_jina-embeddings-v2-small-en-50-gpt-3.5-turbo-01_8647177611). | |
| ## 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 = "fine-tuned/medical-10-10-1-jinaai_jina-embeddings-v2-small-en-50-gpt-3.5-turbo-01_8647177611" | |
| tokenizer = AutoTokenizer.from_pretrained(llm_name) | |
| model = AutoModel.from_pretrained(llm_name, trust_remote_code=True) | |
| tokens = tokenizer("Your text here", return_tensors="pt") | |
| embedding = model(**tokens) | |
| ``` | |