Instructions to use concedo/KobbleTinyV2-1.1B-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 concedo/KobbleTinyV2-1.1B-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 concedo/KobbleTinyV2-1.1B-GGUF:Q6_K # Run inference directly in the terminal: llama cli -hf concedo/KobbleTinyV2-1.1B-GGUF:Q6_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf concedo/KobbleTinyV2-1.1B-GGUF:Q6_K # Run inference directly in the terminal: llama cli -hf concedo/KobbleTinyV2-1.1B-GGUF:Q6_K
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 concedo/KobbleTinyV2-1.1B-GGUF:Q6_K # Run inference directly in the terminal: ./llama-cli -hf concedo/KobbleTinyV2-1.1B-GGUF:Q6_K
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 concedo/KobbleTinyV2-1.1B-GGUF:Q6_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf concedo/KobbleTinyV2-1.1B-GGUF:Q6_K
Use Docker
docker model run hf.co/concedo/KobbleTinyV2-1.1B-GGUF:Q6_K
- LM Studio
- Jan
- Ollama
How to use concedo/KobbleTinyV2-1.1B-GGUF with Ollama:
ollama run hf.co/concedo/KobbleTinyV2-1.1B-GGUF:Q6_K
- Unsloth Studio
How to use concedo/KobbleTinyV2-1.1B-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 concedo/KobbleTinyV2-1.1B-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 concedo/KobbleTinyV2-1.1B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for concedo/KobbleTinyV2-1.1B-GGUF to start chatting
- Docker Model Runner
How to use concedo/KobbleTinyV2-1.1B-GGUF with Docker Model Runner:
docker model run hf.co/concedo/KobbleTinyV2-1.1B-GGUF:Q6_K
- Lemonade
How to use concedo/KobbleTinyV2-1.1B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull concedo/KobbleTinyV2-1.1B-GGUF:Q6_K
Run and chat with the model
lemonade run user.KobbleTinyV2-1.1B-GGUF-Q6_K
List all available models
lemonade list
- Atomic Chat
This is the GGUF quantization of https://huggingface.co/concedo/KobbleTiny
You can use KoboldCpp to run this model. With only 1B parameters, this model is ideal for running on mobile or low-end devices.
Update: KobbleTiny has been upgraded to V2! The old V1 GGUF is still available at this link.
Try it live now: https://concedo-koboldcpp-kobbletiny.hf.space/
Dataset and Objectives
The Kobble Dataset is a semi-private aggregated dataset made from multiple online sources and web scrapes. It contains content chosen and formatted specifically to work with KoboldAI software and Kobold Lite.
Dataset Categories:
- Instruct: Single turn instruct examples presented in the Alpaca format, with an emphasis on uncensored and unrestricted responses.
- Chat: Two participant roleplay conversation logs in a multi-turn raw chat format that KoboldAI uses.
- Story: Unstructured fiction excerpts, including literature containing various erotic and provocative content.
Prompt template: Alpaca
### Instruction:
{prompt}
### Response:
Note: No assurances will be provided about the origins, safety, or copyright status of this model, or of any content within the Kobble dataset.
If you belong to a country or organization that has strict AI laws or restrictions against unlabelled or unrestricted content, you are advised not to use this model.
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