Instructions to use gaianet/vitalik.eth-7b 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 gaianet/vitalik.eth-7b 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 gaianet/vitalik.eth-7b:F16 # Run inference directly in the terminal: llama cli -hf gaianet/vitalik.eth-7b:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf gaianet/vitalik.eth-7b:F16 # Run inference directly in the terminal: llama cli -hf gaianet/vitalik.eth-7b:F16
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf gaianet/vitalik.eth-7b:F16 # Run inference directly in the terminal: ./build/bin/llama cli -hf gaianet/vitalik.eth-7b:F16
Use Docker
docker model run hf.co/gaianet/vitalik.eth-7b:F16
- Llama new
- LM Studio
- Jan
- Ollama
How to use gaianet/vitalik.eth-7b with Ollama:
ollama run hf.co/gaianet/vitalik.eth-7b:F16
- Unsloth Desktop
- Docker Model Runner
How to use gaianet/vitalik.eth-7b with Docker Model Runner:
docker model run hf.co/gaianet/vitalik.eth-7b:F16
- Lemonade
How to use gaianet/vitalik.eth-7b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull gaianet/vitalik.eth-7b:F16
Run and chat with the model
lemonade run user.vitalik.eth-7b-F16
List all available models
lemonade list
- Atomic Chat
Prerequisites
The vitalik-7b.csv file contains the QA set required for the fine-tuning. The convert.py script converts the CSV file into QAs in the llama2 chat template.
python convert.py
It generates a vitalik-7b.txt file, which can now be used in fine-tuning.
Fine-tuning steps
Clone this repo into the llama.cpp/models/ folder.
cd llama.cpp/models
git clone https://huggingface.co/gaianet/vitalik.eth-7b
Move the Llama2-7b-chat base model to the folder.
cd vitalik-7b
mv path/to/llama-2-7b-chat.Q5_K_M.gguf .
From the llama.cpp/models/vitalik-7b folder run the following command.
../../build/bin/finetune --model-base llama-2-7b-chat.Q5_K_M.gguf --lora-out lora.bin --train-data vitalik-7b.txt --sample-start '<SFT>' --adam-iter 1024
Wait for several days until the above process finishes. You will have a lora.bin file, which can generate the fine-tuned model.
../../build/bin/export-lora --model-base llama-2-7b-chat.Q5_K_M.gguf --lora lora.bin --model-out vitalik.eth-7b-q5_k_m.gguf
Learn more about Llama2 model fine tuning here.
Run with Gaianet
Prompt template:
prompt template: llama-2-chat
Context size:
chat_ctx_size: 4096
Run with GaiaNet:
Quick start: https://docs.gaianet.ai/node-guide/quick-start
Customize your node: https://docs.gaianet.ai/node-guide/customize
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