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Docubrief Qwen2.5 1.5b

Fine-tuned with QLoRA on 4000 examples derived from CNN/DailyMail.

KindOtherBase modelQwen/Qwen2.5-1.5B-InstructVersionRevision 872b33e

Model source

Kind
Other
File size
2.88 GB
Base model
Qwen/Qwen2.5-1.5B-Instruct
Version
vRevision 872b33e
Updated
Sep 28, 2026
Downloads
14
Source
Hugging Face

Source description

DocuBrief — Document Summarization Assistant (fine-tuned Qwen/Qwen2.5-1.5B-Instruct)

Fine-tuned with QLoRA on 4000 examples derived from CNN/DailyMail.

Intended use

Designed to be paired with a RAG/chunking layer that supplies the actual document content at inference time (see the DocuBrief AI project guide). This model provides the summarization behavior - clear, well-structured, faithful summaries - not memorized knowledge of any particular document.

Training

  • Base model: Qwen/Qwen2.5-1.5B-Instruct
  • Method: QLoRA (4-bit NF4), r=16, alpha=32
  • Steps: 200, LR: 2e-4, max seq len: 1024
  • Dataset: CNN/DailyMail 3.0.0, articles truncated to <= 500 words

Limitations

  • English only. Small model - pair with the map-reduce/RAG layer described in the DocuBrief AI project guide for accurate summarization of large or arbitrary documents.
  • Trained on news-style text; may need a larger base model or more training for highly technical or domain-specific documents (legal, medical, scientific).

Sources

1 source
Hugging FacePrimaryVersion 872b33eb4daf8ec31ed7160c469e619f19f3eece
huggingface.co/samandar1105/docubrief-qwen2.5-1.5b/tree/872b33eb4daf8ec31ed7160c469e619f19f3eece

Verified Sep 22

Model artifacts

1 artifact

model.safetensors

safetensors · 2.88 GB · SHA-256 6d61f769d405…e3f8 · Hugging Face

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Source excerpts

2 excerpts

--- license: apache-2.0 base_model: Qwen/Qwen2.5-1.5B-Instruct tags: - summarization - lora - qlora - rag datasets: - abisee/cnn_dailymail language: en --- # DocuBrief — Document Summarization Assistant (fine-tuned Qwen/Qwen2.5-1.5B-Instruct) Fine-tuned with QLoRA on 4000 examples derived from [CNN/DailyMail](https://huggingface.co/datasets/abisee/cnn_dailymail). ## Intended use Designed to be paired with a RAG/chunking layer that supplies the actual document content at inference time (see the DocuBrief AI project guide). This model provides the *summarization behavior* - clear, well-structured, faithful summaries - not memorized knowledge of any particular document. ## Training - Base model: `Qwen/Qwen2.5-1.5B-Instruct` - Method: QLoRA (4-bit NF4), r=16, alpha=32 - Steps: 200, LR: 2e-4, max seq len: 1024 - Dataset: CNN/DailyMail 3.0.0, articles truncated to <= 500 words ## Limitations - English only. Small model - pair with the map-reduce/RAG layer described in the DocuBrief AI project guide for accurate summarization of large or arbitrary documents. - Trained on news-style text; may need a larger base model or more training for highly technical or domain-specific documents (legal, medical, scientific).

Source context: 14 downloads · 0 likes · Pipeline summarization · Repo samandar1105/docubrief-qwen2.5-1.5b