Get a weekly rundown of the latest AI models and research... subscribe! https://aimodels.substack.com/

Flan Alpaca Xxl

declare-lab

๐Ÿ“ถ

๐Ÿฎ ๐Ÿฆ™ Flan-Alpaca: Instruction Tuning from Humans and Machines ๐Ÿ“ฃ We developed Flacuna by fine-tuning Vicuna-13B on the Flan collection. Flacuna is better than Vicuna at problem-solving. Access the model here https://huggingface.co/declare-lab/flacuna-13b-v1.0. ๐Ÿ“ฃ Curious to know the performance of ๐Ÿฎ ๐Ÿฆ™ Flan-Alpaca on large-scale LLM evaluation benchmark, InstructEval? Read our paper https://arxiv.org/pdf/2306.04757.pdf. We evaluated more than 10 open-source instruction-tuned LLMs belonging to various LLM families including Pythia, LLaMA, T5, UL2, OPT, and Mosaic. Codes and datasets: https://github.com/declare-lab/instruct-eval ๐Ÿ“ฃ FLAN-T5 is also useful in text-to-audio generation. Find our work at https://github.com/declare-lab/tango if you are interested. Our repository contains code for extending the Stanford Alpaca synthetic instruction tuning to existing instruction-tuned models such as Flan-T5. We have a live interactive demo thanks to Joao Gante! We are also benchmarking many instruction-tuned models at declare-lab/flan-eval. Our pretrained models are fully available on HuggingFace ๐Ÿค— : *recommended for better performance Why? Alpaca represents an exciting new direction to approximate the performance of large language models (LLMs) like ChatGPT cheaply and easily. Concretely, they leverage an LLM such as GPT-3 to generate instructions as synthetic training data. The synthetic data which covers more than 50k tasks can then be used to finetune a smaller model. However, the original implementation is less accessible due to licensing constraints of the underlying LLaMA model. Furthermore, users have noted potential noise in the synthetic dataset. Hence, it may be better to explore a fully accessible model that is already trained on high-quality (but less diverse) instructions such as Flan-T5. Usage
text2text-generation

Pricing

Cost per run
$-
USD
Avg run time
-
Seconds
Hardware
-
Prediction

Creator Models

ModelCostRuns
Tango Full$?5
Tango Full Ft Audiocaps$?178
Segue W2v2 Base$?254
Flan Gpt4all Xl$?428
Tango Full Ft Audio Music Caps$?0

Similar Models

Try it!

You can use this area to play around with demo applications that incorporate the Flan Alpaca Xxl model. These demos are maintained and hosted externally by third-party creators. If you see an error, message me on Twitter.

Currently, there are no demos available for this model.

Overview

Summary of this model and related resources.

PropertyValue
Creatordeclare-lab
Model NameFlan Alpaca Xxl
Description

๐Ÿฎ ๐Ÿฆ™ Flan-Alpaca: Instruction Tuning from Humans and Machines ...

Read more ยป
Tagstext2text-generation
Model LinkView on HuggingFace
API SpecView on HuggingFace
Github LinkNo Github link provided
Paper LinkNo paper link provided

Popularity

How popular is this model, by number of runs? How popular is the creator, by the sum of all their runs?

PropertyValue
Runs1,654
Model Rank
Creator Rank

Cost

How much does it cost to run this model? How long, on average, does it take to complete a run?

PropertyValue
Cost per Run$-
Prediction Hardware-
Average Completion Time-