README.md

metadata

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.

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 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)