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MODEL Listed

flan t5 small

Flan-T5 Small is a lightweight, encoder-decoder model designed for efficient text-to-text generation. Unlike the base T5, the Flan version is instruction-tuned, meaning it performs significantly better on zero-shot tasks without requiring extensive fine-tuning. For developers, this model is an ideal choice for low-latency applications or edge deployment where memory is constrained. It excels at focused NLP tasks such as classification, basic summarization, and question answering. While it lacks the reasoning depth of larger LLMs, its small footprint makes it an excellent candidate for distillation targets or as a specialized component within a larger modular pipeline via the Hugging Face Transformers library.

googletext2text-generation
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01 / MODEL CARD

Model card

Flan-T5 Small is a lightweight, encoder-decoder model designed for efficient text-to-text generation. Unlike the base T5, the Flan version is instruction-tuned, meaning it performs significantly better on zero-shot tasks without requiring extensive fine-tuning. For developers, this model is an ideal choice for low-latency applications or edge deployment where memory is constrained. It excels at focused NLP tasks such as classification, basic summarization, and question answering. While it lacks the reasoning depth of larger LLMs, its small footprint makes it an excellent candidate for distillation targets or as a specialized component within a larger modular pipeline via the Hugging Face Transformers library.

Model typetext2text-generation
Providergoogle
Licenseapache-2.0
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/google/flan-t5-small
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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: google/flan-t5-small
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 google/flan-t5-small
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 google/flan-t5-small 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('google/flan-t5-small')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/google/flan-t5-small.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/google/flan-t5-small.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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