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--- |
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license: mit |
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datasets: |
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- fine-tuned/jina-embeddings-v2-base-en-03052024-im2p-webapp |
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language: |
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- en |
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- en |
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- en |
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- en |
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- en |
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- en |
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- en |
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pipeline_tag: feature-extraction |
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tags: |
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- sentence-transformers |
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- PyTorch |
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- Core ML |
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- ONNX |
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- allenai/c4 |
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- sentence-similarity |
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- feature-extraction |
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- Toys |
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- Children |
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- Games |
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- Educational |
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- Entertainment |
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--- |
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The model is a fine-tuned version of jinaai/jina-embeddings-v2-base-en designed for the following use case: |
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This model is designed to support various applications in natural language processing and understanding. |
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## How to Use |
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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: |
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```python |
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from transformers import AutoModel, AutoTokenizer |
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llm_name = "jina-embeddings-v2-base-en-03052024-im2p-webapp" |
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tokenizer = AutoTokenizer.from_pretrained(llm_name) |
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model = AutoModel.from_pretrained(llm_name, trust_remote_code=True) |
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tokens = tokenizer("Your text here", return_tensors="pt") |
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embedding = model(**tokens) |
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``` |
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