Sentence Similarity
sentence-transformers
Safetensors
English
feature-extraction
grant-matching
nonprofit
foundation-grants
Instructions to use ArkMaster123/grantpilot-embedding-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ArkMaster123/grantpilot-embedding-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ArkMaster123/grantpilot-embedding-v2") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
V2 embedding model (federal + foundation) - training_config.json
Browse files- training_config.json +9 -0
training_config.json
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{
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"base_model": "Qwen/Qwen3-Embedding-0.6B",
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"max_steps": 1000,
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"batch_size": 32,
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"learning_rate": 2e-05,
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"lora_r": 16,
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"lora_alpha": 32,
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"embedding_dim": 1024
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}
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