Instructions to use brittlewis12/h2o-danube-1.8b-chat-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use brittlewis12/h2o-danube-1.8b-chat-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf brittlewis12/h2o-danube-1.8b-chat-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf brittlewis12/h2o-danube-1.8b-chat-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf brittlewis12/h2o-danube-1.8b-chat-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf brittlewis12/h2o-danube-1.8b-chat-GGUF:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf brittlewis12/h2o-danube-1.8b-chat-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf brittlewis12/h2o-danube-1.8b-chat-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf brittlewis12/h2o-danube-1.8b-chat-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf brittlewis12/h2o-danube-1.8b-chat-GGUF:Q4_K_M
Use Docker
docker model run hf.co/brittlewis12/h2o-danube-1.8b-chat-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use brittlewis12/h2o-danube-1.8b-chat-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "brittlewis12/h2o-danube-1.8b-chat-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "brittlewis12/h2o-danube-1.8b-chat-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/brittlewis12/h2o-danube-1.8b-chat-GGUF:Q4_K_M
- Ollama
How to use brittlewis12/h2o-danube-1.8b-chat-GGUF with Ollama:
ollama run hf.co/brittlewis12/h2o-danube-1.8b-chat-GGUF:Q4_K_M
- Unsloth Studio
How to use brittlewis12/h2o-danube-1.8b-chat-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for brittlewis12/h2o-danube-1.8b-chat-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for brittlewis12/h2o-danube-1.8b-chat-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for brittlewis12/h2o-danube-1.8b-chat-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use brittlewis12/h2o-danube-1.8b-chat-GGUF with Docker Model Runner:
docker model run hf.co/brittlewis12/h2o-danube-1.8b-chat-GGUF:Q4_K_M
- Lemonade
How to use brittlewis12/h2o-danube-1.8b-chat-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull brittlewis12/h2o-danube-1.8b-chat-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.h2o-danube-1.8b-chat-GGUF-Q4_K_M
List all available models
lemonade list
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 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!
- make it your own with custom Theme colors
- 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 |
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Model tree for brittlewis12/h2o-danube-1.8b-chat-GGUF
Base model
h2oai/h2o-danube-1.8b-chat
docker model run hf.co/brittlewis12/h2o-danube-1.8b-chat-GGUF: