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Rebine
/
Etsu-Embedding-0.8B

Feature Extraction
Transformers
Safetensors
qwen3_5_text
embeddings
sentence-similarity
information-retrieval
memory-retrieval
chinese
etsu
qwen3.5
Model card Files Files and versions
xet
Community

Instructions to use Rebine/Etsu-Embedding-0.8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Rebine/Etsu-Embedding-0.8B with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="Rebine/Etsu-Embedding-0.8B")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("Rebine/Etsu-Embedding-0.8B")
    model = AutoModel.from_pretrained("Rebine/Etsu-Embedding-0.8B", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Etsu-Embedding-0.8B
1.52 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 11 commits
Rebine's picture
Rebine
Add training data disclosure: sources, SHA-256, benchmark overlap audit
f035293 verified 12 days ago
  • .gitattributes
    1.57 kB
    Upload final OpenClaw memory embedding model 2 months ago
  • README.md
    8.23 kB
    Add training data disclosure: sources, SHA-256, benchmark overlap audit 12 days ago
  • chat_template.jinja
    7.76 kB
    Upload final OpenClaw memory embedding model 2 months ago
  • config.json
    1.79 kB
    Align max_position_embeddings with training context (2048) 2 months ago
  • embedding_config.json
    344 Bytes
    Upload final OpenClaw memory embedding model 2 months ago
  • model.safetensors
    1.5 GB
    xet
    Upload final OpenClaw memory embedding model 2 months ago
  • tokenizer.json
    20 MB
    xet
    Upload final OpenClaw memory embedding model 2 months ago
  • tokenizer_config.json
    1.32 kB
    Upload final OpenClaw memory embedding model 2 months ago