GGUF quantized version for local inference (llama.cpp, LM Studio CLI) This is a GGUF quantized version of: KellanF89/Newton-Insights-V1-cannabis-extraction-science

The model is a domain-specific language model trained on cannabis science literature, focusing on:

extraction techniques
terpene and cannabinoid chemistry
pharmacology
cultivation

This version was converted and quantized for local inference using llama.cpp-compatible runtimes.

Model Details

Developed by: Kellan Finney / Eighth Revolution (original model)
Model type: Causal Language Model (fine-tuned)
Language: English
License: Apache 2.0
Finetuned from: IBM Granite 3.0 8B Instruct

Available Quantizations

File	Quant	Size	Notes
Newton-Insights-V1-cannabis-extraction-science-q4_k_m.gguf	Q4_K_M	~4-5 GB	Good balance, lower VRAM
Newton-Insights-V1-cannabis-extraction-science-q5_k_m.gguf	Q5_K_M	~5-6 GB	Recommended
Newton-Insights-V1-cannabis-extraction-science-q6_k.gguf	Q6_K	~6-7 GB	Higher quality
Newton-Insights-V1-cannabis-extraction-science-f16.gguf	F16	~16 GB	Full precision

Uses

Direct Use

Domain-specific Q&A about cannabis science
Educational and research purposes
Local inference setups (offline AI, homelab, experimentation)

Out-of-Scope Use

Medical advice or treatment recommendations
Legal interpretation
Safety-critical decisions

Limitations

The model may reflect inconsistencies in cannabis terminology (e.g., sativa vs. indica classification).
Not all responses are guaranteed to be scientifically accurate despite domain fine-tuning.
Performance may vary depending on prompt formatting and frontend compatibility (Granite-based models use non-standard chat templates).

How to Use

llama.cpp

./main -m ewald1976/Newton-Insights-V1-cannabis-extraction-science-Q5_K_M.gguf -p "Explain terpene preservation in extraction"

ewald1976/Newton-Insights-V1-cannabis-extraction-science-gguf

Note on source files

Newton Insights V1 – Cannabis Extraction Science (GGUF)

Model Description