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base_model: h2oai/h2o-danube-1.8b-chat
datasets:
  - HuggingFaceH4/ultrafeedback_binarized
  - Intel/orca_dpo_pairs
  - argilla/distilabel-math-preference-dpo
  - Open-Orca/OpenOrca
  - OpenAssistant/oasst2
  - HuggingFaceH4/ultrachat_200k
  - meta-math/MetaMathQA
license: apache-2.0
language:
  - en
model_creator: h2oai
model_name: h2o-danube-1.8b-chat
model_type: mistral
inference: false
tags:
  - gpt
  - llm
  - large language model
  - h2o-llmstudio
pipeline_tag: text-generation
prompt_template: |
  <|system|>{{system_message}}</s>
  <|prompt|>{{prompt}}</s>
  <|answer|>
quantized_by: brittlewis12

h2o-danube-1.8b-chat GGUF

Original model: h2o-danube-1.8b-chat Model creator: h2oai

This repo contains GGUF format model files for h2oai’s h2o-danube-1.8b-chat.

h2o-danube-1.8b-chat is an chat fine-tuned model by H2O.ai with 1.8 billion parameters. For details, please refer to our Technical Report. We release three versions of this model:

  • h2oai/h2o-danube-1.8b-base Base model
  • h2oai/h2o-danube-1.8b-sft SFT tuned
  • h2oai/h2o-danube-1.8b-chat SFT + DPO tuned

We adjust the Llama 2 architecture for a total of around 1.8b parameters. We use the original Llama 2 tokenizer with a vocabulary size of 32,000 and train our model up to a context length of 16,384. We incorporate the sliding window attention from mistral with a size of 4,096.

Refer to h2o.ai’s model disclaimer for terms of use.

What is GGUF?

GGUF is a file format for representing AI models. It is the third version of the format, introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. Converted using llama.cpp b2037 (1cfb537)

Prompt template:

<|system|>{{system_message}}</s>
<|prompt|>{{prompt}}</s>
<|answer|>

Download & run with cnvrs on iPhone, iPad, and Mac!

cnvrs.ai

cnvrs is the best app for private, local AI on your device:

  • create & save Characters with custom system prompts & temperature settings
  • download and experiment with any GGUF model you can find on HuggingFace!
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  • powered by Metal ⚡️ & Llama.cpp, with haptics during response streaming!
  • try it out yourself today, on Testflight!
  • follow cnvrs on twitter to stay up to date

Original Model Evaluations:

Commonsense, world-knowledge and reading comprehension tested in 0-shot:

Benchmark acc_n
ARC-easy 67.51
ARC-challenge 39.25
BoolQ 77.89
Hellaswag 67.60
OpenBookQA 39.20
PiQA 76.71
TriviaQA 36.29
Winogrande 65.35