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models Text Generation documentation
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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 ...
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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...
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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...
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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 ...
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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 ...