yi-34b-200k

Maintainer: 01-ai

Total Score

1

Last updated 6/13/2024
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Model overview

The yi-34b is a large language model trained from scratch by developers at 01.AI. It is part of the Yi series models, which are targeted as bilingual language models and trained on a 3T multilingual corpus. The Yi series models show promise in language understanding, commonsense reasoning, reading comprehension, and more.

The yi-34b-chat is a chat model based on the yi-34b base model, which has been fine-tuned using a Supervised Fine-Tuning (SFT) approach. This results in responses that mirror human conversation style more closely compared to the base model.

The yi-6b is a smaller version of the Yi series models, with a parameter size of 6 billion. It is suitable for personal and academic use.

Model inputs and outputs

The Yi models accept natural language prompts as input and generate continuations of the prompt as output. The models can be used for a variety of natural language processing tasks, such as text generation, question answering, and language understanding.

Inputs

  • Prompt: The input text that the model should use to generate a continuation.
  • Temperature: A value that controls the "creativity" of the model's outputs, with higher values generating more diverse and unpredictable text.
  • Top K: The number of highest probability tokens to consider for generating the output.
  • Top P: A probability threshold for generating the output, keeping only the top tokens with cumulative probability above the threshold.

Outputs

  • Generated text: The model's continuation of the input prompt, generated token-by-token.

Capabilities

The Yi series models, particularly the yi-34b and yi-34b-chat, have demonstrated impressive performance on a range of benchmarks. The yi-34b-chat model ranked second on the AlpacaEval Leaderboard, outperforming other large language models like GPT-4, Mixtral, and Claude.

The yi-34b and yi-34b-200K models have also performed exceptionally well on the Hugging Face Open LLM Leaderboard (pre-trained) and C-Eval, ranking first among all existing open-source models in both English and Chinese.

What can I use it for?

The Yi series models can be used for a variety of natural language processing tasks, such as:

  • Content generation: The models can be used to generate diverse and engaging text, including stories, articles, and poems.
  • Question answering: The models can be used to answer questions on a wide range of topics, drawing on their broad knowledge base.
  • Language understanding: The models can be used to analyze and understand natural language, with applications in areas like sentiment analysis and text classification.

Things to try

One interesting thing to try with the Yi models is to experiment with different input prompts and generation parameters to see how the models respond. For example, you could try prompting the models with open-ended questions or creative writing prompts, and observe the diverse range of responses they generate.

You could also explore the models' capabilities in specialized domains, such as code generation or mathematical problem-solving, by providing them with relevant prompts and evaluating their performance.



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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