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StableLM won the 2021 OSC China Open Source Project Selection "The Best Popularity Project" !
Authorization Agreement Apache-2.0
development language Python View source code »
operating system Cross platform
Software type Open source software
Open source organizations nothing
region Unknown
deliverer Alias_Travis
intended for unknown
Recording time 2023-04-20

Software Introduction

The StableLM project warehouse contains the StableLM series language models being developed by Stability AI. At present, Stability AI has released the initial StableLM alpha model set, with 3 billion and 7 billion parameters. Models with 15 billion and 30 billion parameters are under development.

Stability AI is currently HuggingFace Spaces A demo version of the 7 billion parameter model, StableLM-Tuned-Alpha-7B, has been released on. Users can visit this website to try it out.

StableLM Alpha model is trained on the basis of the expanded version of the Pile dataset, which contains 1.5 trillion tokens. The expanded version dataset is about three times the size of the Pile.

Size StableLM-Base-Alpha StableLM-Tuned-Alpha Training Tokens Parameters Web Demo
3B checkpoint checkpoint 800B 3,638,525,952  
7B checkpoint checkpoint 800B 7,869,358,080 HuggingFace
15B have in hand (pending)      
30B have in hand (pending)      
65B have in hand (pending)      
175B (planned)        
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Published information
2023/10/03 12:35

Stability AI releases the latest language model: Stable LM 3B

Stability AI released the latest language model yesterday: Stable LM 3B, which can run on smart devices such as laptops and mobile phones. The announcement wrote that Stable LM 3B contains 3 billion parameters, which is smaller and more efficient than the 7 billion parameters commonly used in the industry. The main functions are as follows: text generation: it can be used to generate text autoregression: training data based on the diversity of converter decoder architecture: multiple open source large-scale data sets are used. Stable LM 3B Main features: high performance: although there are only 3 billion parameters, the performance is equivalent to or even exceeds that of larger models. Low power consumption: design

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