Model: teapotai/teapotllm
Author: teapotai
Pipeline: text-generation
Library: transformers
Tags: transformers, onnx, safetensors, t5, text2text-generation, text-generation, transformers.js, en, fr, ro, de, multilingual, dataset:teapotai/synthqa, dataset:teapotai/teapot-chat, base_model:google/flan-t5-large, base_model:quantized:google/flan-t5-large, license:mit, text-generation-inference, endpoints_compatible, region:us
Base models (quantized): id: google/flan-t5-large
Card metadata: license: mit
datasets: teapotai/synthqa, teapotai/teapot-chat
language: en, fr, ro, de, multilingual
library_name: transformers
tags: text-generation, transformers.js
widget: text: Teapot is an open-source small language model (~800 million parameters) fine-tuned on synthetic data and optimized to run locally on resource-constrained devices such as smartphones and CPUs. Teapot is trained to only answer using context from documents, reducing hallucinations. Teapot can perform a variety of tasks, including hallucination-resistant Question Answering (QnA), Retrieval-Augmented Generation (RAG), and JSON extraction. TeapotLLM is a fine tune of flan-t5-large that was trained on synthetic data generated by Deepseek v3 TeapotLLM can be hosted on low-power devices with as little as 2GB of CPU RAM such as a Raspberry Pi. Teapot is a model built by and for the community.

What devices can teapot run on?
example_title: Question Answering, text: Teapot is an open-source small language model (~800 million parameters) fine-tuned on synthetic data and optimized to run locally on resource-constrained devices such as smartphones and CPUs. Teapot is trained to only answer using context from documents, reducing hallucinations. Teapot can perform a variety of tasks, including hallucination-resistant Question Answering (QnA), Retrieval-Augmented Generation (RAG), and JSON extraction. TeapotLLM is a fine tune of flan-t5-large that was trained on synthetic data generated by Deepseek v3 TeapotLLM can be hosted on low-power devices with as little as 2GB of CPU RAM such as a Raspberry Pi. Teapot is a model built by and for the community.

Tell me about teapotllm 
example_title: Summarization Answering, text: Teapot is an open-source small language model (~800 million parameters) fine-tuned on synthetic data and optimized to run locally on resource-constrained devices such as smartphones and CPUs. Teapot is trained to only answer using context from documents, reducing hallucinations. Teapot can perform a variety of tasks, including hallucination-resistant Question Answering (QnA), Retrieval-Augmented Generation (RAG), and JSON extraction. TeapotLLM is a fine tune of flan-t5-large that was trained on synthetic data generated by Deepseek v3 TeapotLLM can be hosted on low-power devices with as little as 2GB of CPU RAM such as a Raspberry Pi. Teapot is a model built by and for the community.

Extract the number of parameters
example_title: Information Extraction, text: Teapot is an open-source small language model (~800 million parameters) fine-tuned on synthetic data and optimized to run locally on resource-constrained devices such as smartphones and CPUs. Teapot is trained to only answer using context from documents, reducing hallucinations. Teapot can perform a variety of tasks, including hallucination-resistant Question Answering (QnA), Retrieval-Augmented Generation (RAG), and JSON extraction. TeapotLLM is a fine tune of flan-t5-large that was trained on synthetic data generated by Deepseek v3 TeapotLLM can be hosted on low-power devices with as little as 2GB of CPU RAM such as a Raspberry Pi. Teapot is a model built by and for the community.

How many parameters is Deepseek? 
example_title: Hallucination Resistance
base_model: google/flan-t5-large
pipeline_tag: text2text-generation
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Created: 2025-01-19 02:29:11