CodeFuse Embeddings

CodeFuse Embeddings is an index of CodeFuse's text and code embedding research repositories, spanning several named embedding model projects and a benchmark.

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CodeFuse Embeddings collects and links to CodeFuse's separate text- and code-embedding research repositories: C2LLM, D2LLM, E2LLM, F2LLM, ML-Embed and CoREB. Each of the linked names is its own embedding-related project or research effort from the CodeFuse group, rather than a single unified codebase in this repository itself.

It is written in Python.

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mini-AGI
github.com
A continual learning language model that trains from scratch on a single 8 GB VRAM GPU, assembling its own architecture and adapting its size to the hardware and data available rather than shipping as a fixed pretrained model.
- Models
Applied Inference Lab: Compliance Control Embedding Stack
github.com
An open-source contrastive-embedding pipeline that maps technical CVE vulnerability descriptions to formal cybersecurity compliance controls in NIST SP 800-53 and CMMC, published with its model generation, fine-tuning and evaluation code.
- Models
- Security
peekaboolean
github.com
A small vision-language model, fine-tuned with LoRA on a 500-million-parameter backbone, that answers typed multiple-choice, ordinal-score and yes/no questions about an image with calibrated probabilities, in about 400 milliseconds on a laptop.
- Models
- Inference

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mini-AGI

Applied Inference Lab: Compliance Control Embedding Stack

peekaboolean

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