models Text Generation documentation - Azure/azureml-assets GitHub Wiki

Text Generation

Models in this category

  • Deci-DeciCoder-1b

    The Model Card for DeciCoder 1B provides details about a 1 billion parameter decoder-only code completion model developed by Deci. The model was trained on Python, Java, and JavaScript subsets of Starcoder Training Dataset and uses Grouped Query Attention with a context window of 2048 tokens. It ...

  • Deci-DeciLM-7B

    DeciLM-7B is a decoder-only text generation model with 7.04 billion parameters, released by Deci under the Apache 2.0 license. It is the top-performing 7B base language model on the Open LLM Leaderboard and uses variable Grouped-Query Attention (GQA) to achieve a superior balance between accuracy...

  • Deci-DeciLM-7B-instruct

    DeciLM-7B-instruct is a model for short-form instruction following, built by LoRA fine-tuning on the SlimOrca dataset. It is a derivative of the recently released DeciLM-7B language model, a pre-trained, high-efficiency generative text model with 7 billion parameters. DeciLM-7B-instruct is one of...

  • microsoft-Orca-2-13b

    Orca 2 is a finetuned version of LLAMA-2. Orca 2’s training data is a synthetic dataset that was created to enhance the small model’s reasoning abilities. All synthetic training data was moderated using the Microsoft Azure content filters. More details about the model can be found in the [Orca 2 ...

  • microsoft-Orca-2-7b

    Orca 2 is a finetuned version of LLAMA-2. Orca 2’s training data is a synthetic dataset that was created to enhance the small model’s reasoning abilities. All synthetic training data was moderated using the Microsoft Azure content filters. More details about the model can be found in the [Orca 2 ...

  • microsoft-phi-1-5

    Microsoft Phi-1.5

Phi-1.5 is a Transformer-based language model with 1.3 billion parameters. It was trained on a combination of data sources, including an additional source of NLP synthetic texts. Phi-1.5 performs exceptionally well on benchmarks testing common sense, language understandi...

The phi-2 is a language model with 2.7 billion parameters. The phi-2 model was trained using the same data sources as phi-1, augmented with a new data source that consists of various NLP synthetic texts and filtered websites (for safety and educational value). When assesse...

Aguila-7b

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FLOR-1.3B

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FLOR-1.3B Instructed

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FLOR-6.3B

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FLOR-6.3B Instructed

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Arctic is a dense-MoE Hybrid transformer architecture pre-trained from scratch by the Snowflake AI Research Team. We are releasing model checkpoints for both the base and instruct-tuned versions of Arctic under an Apache-2.0 license. This means you can use them freely in your ow...

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