How do I turn a HuggingFace model into a GGUF file?
Pull the model from the Hub, then convert and quantize it to GGUF with llama.cpp. a2a.computer plans this as a two-hop governed path and can realize each hop with an evidence receipt.
from hub_repoto gguf
Available paths (live from the planner)
#12 hopsloss 15%~300srisk high
hub_repo→pull→hf_dir→quantize_to_gguf→gguf
How a2a.computer knows this
The path below is produced live by the transmutation-planner over the real capability graph — each hop is a governed CHP capability, not a suggestion. Loss and cost are the planner's declared edge estimates; realizing a hop emits a signed evidence record.
For agents
Capabilities:
chp.adapters.huggingface.pullchp.adapters.huggingface.quantize_to_ggufMCP tools:
find_transmutation_pathsestimate_transmutationrealize_stateretrieve_evidenceLimitations & uncertainty
- –Quantization is lossy — the planner reports the expected quality loss; pick the quant (Q4_K_M, Q8_0, …) to trade size against fidelity.
- –Cost and latency are static estimates, not per-host measurements (per-host figures are a planned enrichment).