hasitha-gallella/live-graph-coder-v1
feature-extraction model by hasitha-gallella
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Model card & documentation
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This Beta release contains only the mixed-precision 6-layer code embedding model: int4 weights with int8 for Q/K/V and embeddings. This attention-based code-search encoder turns code and natural-language queries into embeddings, so a question can find the code it is about. At 66 MB, it is light enough to run on a CPU. Used in the VS Code extension Live Graph Coder (Beta V1): install it for free from the VS Code Marketplace. Queries start with Represent this query for searching relevant code: ; code is embedded as is. The same file runs in Node.js and in browsers with onnxruntime-web. Two benchmarks whose code was not used in training: The…
Read the full model card ↗ · Preview checked 2026-10-30T08:39:32.029Z
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Model overview
hasitha-gallella/live-graph-coder-v1 is a feature-extraction model repository published by hasitha-gallella on Hugging Face. The source reports the onnx library.
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Model facts
- Task
- feature-extraction
- Library
- onnx
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2026-10-21T06:15:12.000Z
- Last modified
- 2026-10-21T06:36:51.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: nomic-ai/CodeRankEmbed
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-21T06:44:13.178Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.