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MODEL Listed

Edge0-35B-A3B-preview

Edge0-35B-A3B-preview is a specialized text-generation model designed for developers seeking a balance between high-performance reasoning and efficient deployment. Built on a 35B parameter architecture, it utilizes an activation-efficient design (A3B) that optimizes throughput without sacrificing the nuance required for complex instruction following. For developers working on edge computing or resource-constrained environments, this model offers a compelling middle ground between lightweight small language models and massive, high-latency frontier models. It is particularly well-suited for RAG pipelines, automated code documentation, and structured data extraction tasks. Since it is released under the Apache-2.0 license, it provides the legal flexibility necessary for commercial integration and fine-tuning. Compared to standard dense models of similar size, the preview architecture aims to deliver lower inference latency, making it a strong candidate for real-time application backends where response speed is as critical as linguistic accuracy.

Edge0text generation
01 / MODEL CARD

Model card

Edge0-35B-A3B-preview is a specialized text-generation model designed for developers seeking a balance between high-performance reasoning and efficient deployment. Built on a 35B parameter architecture, it utilizes an activation-efficient design (A3B) that optimizes throughput without sacrificing the nuance required for complex instruction following. For developers working on edge computing or resource-constrained environments, this model offers a compelling middle ground between lightweight small language models and massive, high-latency frontier models. It is particularly well-suited for RAG pipelines, automated code documentation, and structured data extraction tasks. Since it is released under the Apache-2.0 license, it provides the legal flexibility necessary for commercial integration and fine-tuning. Compared to standard dense models of similar size, the preview architecture aims to deliver lower inference latency, making it a strong candidate for real-time application backends where response speed is as critical as linguistic accuracy.

Model typetext generation
ProviderEdge0
Licenseapache-2.0
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/Edge0/Edge0-35B-A3B-preview
View model source
Version informationUse the source repository for the latest version
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03 / DOWNLOAD

Download this model

We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.

This entry points to Hugging Face. The commands use the matching ModelScope repository format; confirm that the repository exists on ModelScope before running them. Model repository: Edge0/Edge0-35B-A3B-preview
Install ModelScope

Install the CLI and SDK dependency before downloading.

pip install modelscope
Download the full model repository

Download the complete weights, configuration and model card.

modelscope download --model Edge0/Edge0-35B-A3B-preview
Download one file to a local directory

README.md is used as an example; replace it with another repository file when needed.

modelscope download --model Edge0/Edge0-35B-A3B-preview README.md --local_dir ./dir
Download with the SDK

Useful in Python projects and automation scripts.

from modelscope import snapshot_download
model_dir = snapshot_download('Edge0/Edge0-35B-A3B-preview')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/Edge0/Edge0-35B-A3B-preview.git
Clone without downloading LFS blobs

Fetch the repository structure first, then pull large files when needed.

GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/Edge0/Edge0-35B-A3B-preview.git
04 / WORKFLOW

How to use

  1. 01
    Step 1

    Read the model card and source information.

  2. 02
    Step 2

    Start with a small, non-sensitive evaluation.

  3. 03
    Step 3

    Review quality, licensing and usage limits.

  4. 04
    Step 4

    Adopt it only after validation.

05 / DISCUSSIONS

Discussions

Use this space to keep checking source information, usage experience and maintenance status.

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