tiny tapas random wtq
Overview
Tiny TAPAS (Random WTQ) is a specialized, lightweight model designed for table-based question answering. Unlike general LLMs that struggle with structured data alignment, this model is optimized to parse tabular formats and retrieve precise answers from cells based on natural language queries. It is particularly effective for developers building data-driven dashboards, automated reporting tools, or internal knowledge bases where users need to query spreadsheets without writing SQL. Given its compact architecture and Apache-2.0 license, it offers a low-latency alternative for edge deployment or integration into microservices where full-scale models would be computationally prohibitive.
Highlights
- Optimized for structured table-to-text question answering
- Low-latency inference suitable for edge deployments
- Permissive Apache-2.0 license for commercial integration
- Efficient alternative to heavy general-purpose LLMs
Usage
Install
# Install Hugging Face transformers
pip install transformers torchSDK Usage
# Load model with transformers
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("lysandre/tiny-tapas-random-wtq")
tokenizer = AutoTokenizer.from_pretrained("lysandre/tiny-tapas-random-wtq")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_hubCLI Download
Download the full repository
Download the full repository
huggingface-cli download lysandre/tiny-tapas-random-wtqDownload 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-wtq config.json --local-dir ./dirSee 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-wtq')Git Download
Make sure git-lfs is installed first
Git Download
git lfs install
git clone https://huggingface.co/lysandre/tiny-tapas-random-wtqTo skip LFS large-file downloads, use:
Skip LFS
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/lysandre/tiny-tapas-random-wtqModel 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 torchLoad the model and run inference
Load the model and run inference
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained('lysandre/tiny-tapas-random-wtq')
tokenizer = AutoTokenizer.from_pretrained('lysandre/tiny-tapas-random-wtq')