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--- |
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dataset_info: |
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features: |
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- name: context |
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dtype: string |
|
- name: name |
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dtype: string |
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- name: embedding |
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sequence: float32 |
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splits: |
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- name: train |
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num_bytes: 717888 |
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num_examples: 202 |
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download_size: 1005715 |
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dataset_size: 717888 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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task_categories: |
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- sentence-similarity |
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language: |
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- es |
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--- |
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|
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# Modelo |
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|
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- "Alibaba-NLP/gte-multilingual-base" |
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|
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Puedes obtener toda la información relacionado con el modelo <a href="https://huggingface.co/Alibaba-NLP/gte-multilingual-base">aquí</a> |
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|
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# Busqueda |
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|
|
```python |
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from sentence_transformers import SentenceTransformer |
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from sentence_transformers.util import cos_sim |
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from datasets import load_dataset |
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import numpy as np |
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|
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model_name = "Alibaba-NLP/gte-multilingual-base" |
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model = SentenceTransformer(model_name, trust_remote_code=True) |
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|
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raw_data = load_dataset('Manyah/incrustaciones') |
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|
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question = "" |
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question_embedding = model.encode(question) |
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|
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sim = [cos_sim(raw_data['train'][i]['embedding'],question_embedding).numpy() for i in range(0,len(raw_data['train']))] |
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|
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index = sim.index(max(sim)) |
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|
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print(raw_data['train'][index]['context']) |
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|
|
``` |
