h2o-danube-1.8b-chat
Maintainer: h2oai
52
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
h2o-danube-1.8b-chat is an AI model developed by h2oai with 1.8 billion parameters. It is a fine-tuned version of the Llama 2 architecture, incorporating sliding window attention from the Mistral model. The model was trained using the H2O LLM Studio. Similar models include the h2ogpt-gm-oasst1-en-2048-falcon-7b-v3 which was also trained by H2O.ai.
Model inputs and outputs
Inputs
- Conversational context: The model accepts conversational messages formatted using the HuggingFace chat template.
Outputs
- Conversational response: The model generates a response to the provided conversation, up to 256 new tokens.
Capabilities
The h2o-danube-1.8b-chat model demonstrates strong performance on various benchmarks, including commonsense reasoning, world knowledge, and reading comprehension tests. It can engage in open-ended conversations and provide informative responses on a wide range of topics.
What can I use it for?
You can use the h2o-danube-1.8b-chat model for building conversational AI applications, virtual assistants, and chatbots. Its broad knowledge and language understanding capabilities make it suitable for tasks such as customer service, question answering, and general-purpose dialogue.
Things to try
One interesting aspect of the h2o-danube-1.8b-chat model is its ability to handle longer input contexts, up to 16,384 tokens. This can enable more coherent and contextual responses in multi-turn conversations. You could experiment with providing the model with detailed prompts or task descriptions to see how it handles more complex inputs and generates relevant, informative responses.
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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