gbstox/agronomy-resources
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How to use gbstox/agronomistral-GGUF with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf gbstox/agronomistral-GGUF:Q5_K_M # Run inference directly in the terminal: llama cli -hf gbstox/agronomistral-GGUF:Q5_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf gbstox/agronomistral-GGUF:Q5_K_M # Run inference directly in the terminal: llama cli -hf gbstox/agronomistral-GGUF:Q5_K_M
# 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 gbstox/agronomistral-GGUF:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf gbstox/agronomistral-GGUF:Q5_K_M
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 gbstox/agronomistral-GGUF:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf gbstox/agronomistral-GGUF:Q5_K_M
docker model run hf.co/gbstox/agronomistral-GGUF:Q5_K_M
How to use gbstox/agronomistral-GGUF with Ollama:
ollama run hf.co/gbstox/agronomistral-GGUF:Q5_K_M
How to use gbstox/agronomistral-GGUF with Docker Model Runner:
docker model run hf.co/gbstox/agronomistral-GGUF:Q5_K_M
How to use gbstox/agronomistral-GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull gbstox/agronomistral-GGUF:Q5_K_M
lemonade run user.agronomistral-GGUF-Q5_K_M
lemonade list
Agronomistral is fine tuned with agronomy information from textbooks, university extension websites, government websites, and agronomic studies.
Agronomistral consistently outperforms the base model, mistralai/Mistral-7B-v0.1 on the agronomy benchmark.
| Model Name | Score | Date Tested |
|---|---|---|
| gpt-4-1106-preview | 83.84% | 2024-01-02 |
| Mixtral-8x7B-Instruct-v0.1 | 75.76% | 2024-01-02 |
| fbn-norm | 74.75% | 2024-01-02 |
| gpt-3.5-turbo | 73.74% | 2024-01-02 |
| OpenHermes-2p5-Mistral-7B | 65.66% | 2024-01-02 |
| AgronoMistral | 58.59% | 2024-01-08 |
| mistral-7b-instruct-v0.1_Q5_K_M | 47.47% | 2024-01-08 |
5-bit
Base model
mistralai/Mistral-7B-v0.1