tiny tapas random sqa

Providerlysandre
Categorytable-question-answering
LicenseApache-2.0
Downloads2.3K
Stars0

Overview

Tiny Tapas Random SQA is a lightweight, specialized model designed for table-based question answering. Unlike general-purpose LLMs that often struggle with structured data alignment, this model is optimized to parse tabular formats and retrieve precise answers from rows and columns. It is particularly useful for developers building data-driven dashboards, automated reporting tools, or internal knowledge bases where users need to query structured datasets using natural language. Given its Apache-2.0 license, it offers high flexibility for commercial integration. While it lacks the broad reasoning of frontier models, its focused architecture provides a more efficient, low-latency alternative for specific table-QA pipelines where token cost and inference speed are critical.

Highlights

  • Optimized for structured table-based question answering
  • Low-latency inference for real-time data retrieval
  • Permissive Apache-2.0 license for commercial deployment
  • Efficient alternative to general-purpose LLMs for tables

Usage

Install
# Install Hugging Face transformers
pip install transformers torch
SDK Usage
# Load model with transformers
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("lysandre/tiny-tapas-random-sqa")
tokenizer = AutoTokenizer.from_pretrained("lysandre/tiny-tapas-random-sqa")

Hugging Face Download

We recommend downloading the model via the Hugging Face CLI or Hub SDK.

Guidance:Before downloading, install huggingface_hub with:

Guidance
pip install -U huggingface_hub

CLI Download

Download the full repository

Download the full repository
huggingface-cli download lysandre/tiny-tapas-random-sqa

Download a single file to a local folder (e.g. config.json into ./dir)

Download a single file to a local folder (e.g. config.json into ./dir)
huggingface-cli download lysandre/tiny-tapas-random-sqa config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

SDK Download
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('lysandre/tiny-tapas-random-sqa')

Git Download

Make sure git-lfs is installed first

Git Download
git lfs install
git clone https://huggingface.co/lysandre/tiny-tapas-random-sqa

To skip LFS large-file downloads, use:

Skip LFS
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/lysandre/tiny-tapas-random-sqa

Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.

PyTorch / Transformers Usage

Install Transformers

Install Transformers
pip install -U transformers torch

Load the model and run inference

Load the model and run inference
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('lysandre/tiny-tapas-random-sqa')
tokenizer = AutoTokenizer.from_pretrained('lysandre/tiny-tapas-random-sqa')
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