stablelm-base-alpha-3b

Maintainer: stabilityai

Total Score

83

Last updated 5/28/2024

🖼️

PropertyValue
Model LinkView on HuggingFace
API SpecView on HuggingFace
Github LinkNo Github link provided
Paper LinkNo paper link provided

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Model overview

StableLM-Base-Alpha is a suite of 3B and 7B parameter decoder-only language models pre-trained on a diverse collection of English and Code datasets. It is designed to push beyond the context window limitations of existing open-source language models. The model was developed by Stability AI.

Similar models include StableLM-Tuned-Alpha, which are fine-tuned versions of the base model built for chat and instruction-following tasks, and StableCode-Completion-Alpha-3B and StableCode-Instruct-Alpha-3B, which are specialized for code completion and instruction-following code generation tasks.

Model inputs and outputs

The StableLM-Base-Alpha models are designed to take in text inputs and generate continuations or completions. The models have a large context window of up to 4096 tokens, allowing them to leverage long-range dependencies in the input text.

Inputs

  • Text prompts: The model takes in arbitrary text prompts as input, which can range from short phrases to long passages.

Outputs

  • Generated text: The model outputs generated text that continues or completes the input prompt. The length of the generated output can be controlled via parameters like max_new_tokens.

Capabilities

The StableLM-Base-Alpha models excel at general text generation tasks, such as writing, summarization, and open-ended question answering. The large context window and powerful language modeling capabilities allow the models to produce coherent and contextually-relevant text.

What can I use it for?

The StableLM-Base-Alpha models can be used for a variety of applications, such as:

  • Content generation: Generating long-form articles, stories, and other types of written content.
  • Summarization: Summarizing long passages of text into concise summaries.
  • Question answering: Answering open-ended questions based on provided context.
  • Conversational AI: Building chatbots and virtual assistants that can engage in natural conversations.

When using the model, it's important to be mindful of potential biases and limitations, and to avoid treating the model outputs as authoritative sources of information.

Things to try

One interesting thing to try with the StableLM-Base-Alpha models is using the large context window to generate coherent and cohesive long-form text. Prompt the model with an engaging opening paragraph and see how it continues the story or expands on the initial idea. You can also experiment with different temperature and sampling settings to adjust the creativity and diversity of the generated text.

Another interesting use case is to leverage the model's strong language understanding capabilities for tasks like question answering or summarization. Provide the model with detailed context and see how it can extract key information and generate concise, relevant responses.

Overall, the StableLM-Base-Alpha models are a powerful and versatile tool for a wide range of natural language processing tasks. By exploring their capabilities and limitations, you can gain valuable insights into the current state of large language models and how they can be applied to real-world problems.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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stablelm-base-alpha-7b

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stablelm-tuned-alpha-3b

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