Model card
needle3 is a specialized text-generation model released by Cactus-Compute under the Apache-2.0 license, making it highly accessible for commercial and open-source integration. While many general-purpose models suffer from 'lost in the middle' phenomena, needle3 is architected to prioritize context retention and precise information retrieval within long-form sequences. For developers, this means more reliable performance in RAG (Retrieval-Augmented Generation) pipelines and complex document analysis tasks where factual accuracy is non-negotiable. Unlike monolithic proprietary APIs, needle3 offers the flexibility of local deployment via Hugging Face, allowing you to fine-tune the weights for specific domain expertise or latency requirements. It is an ideal candidate for building agentic workflows that require high-fidelity reasoning over large datasets without the overhead of massive parameter counts found in larger frontier models.
Model files and versions
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.
Cactus-Compute/needle3Install the CLI and SDK dependency before downloading.
pip install modelscopeDownload the complete weights, configuration and model card.
modelscope download --model Cactus-Compute/needle3README.md is used as an example; replace it with another repository file when needed.
modelscope download --model Cactus-Compute/needle3 README.md --local_dir ./dirUseful in Python projects and automation scripts.
from modelscope import snapshot_download
model_dir = snapshot_download('Cactus-Compute/needle3')Make sure Git LFS is installed correctly.
git lfs install
git clone https://www.modelscope.cn/Cactus-Compute/needle3.gitFetch the repository structure first, then pull large files when needed.
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/Cactus-Compute/needle3.gitHow to use
- 01Step 1
Read the model card and source information.
- 02Step 2
Start with a small, non-sensitive evaluation.
- 03Step 3
Review quality, licensing and usage limits.
- 04Step 4
Adopt it only after validation.
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