---
license: mit
datasets:
- fine-tuned/jina-embeddings-v2-base-en-02052024-jkqyd3174i-webapp_3375412925
language:
- en
pipeline_tag: feature-extraction
tags:
- guitar
- sentence-transformers
model-index:
- name: Yi-34B
  results:
  - task:
      type: text-generation
    dataset:
      name: ai2_arc
      type: ai2_arc
    metrics:
    - name: AI2 Reasoning Challenge (25-Shot)
      type: AI2 Reasoning Challenge (25-Shot)
      value: 64.59
    source:
      name: Open LLM Leaderboard
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
---
# fine-tuned/jina-embeddings-v2-base-en-522024-6pj3-webapp_6103321184

## Model Description

fine-tuned/jina-embeddings-v2-base-en-522024-6pj3-webapp_6103321184 is a fine-tuned version of jinaai/jina-embeddings-v2-base-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/jina-embeddings-v2-base-en-522024-6pj3-webapp_6103321184).

## 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/jina-embeddings-v2-base-en-522024-6pj3-webapp_6103321184"
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)
```