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.TH HF_TO_NVFP4_GGUF 1 "November 2026" "nvfp4_gguf_quant" "User Commands"
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.SH NAME
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hf_to_nvfp4_gguf \- quantize Hugging Face models to NVFP4 GGUF for llama.cpp and Ollama
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.SH SYNOPSIS
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.B hf_to_nvfp4_gguf
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[\fB\-o\fR \fIOUTPUT\fR]
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[\fB\-\-modelfile\-only\fR]
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[\fB\-\-overwrite\fR]
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[\fB\-\-mmproj\fR \fIMMPROJ\fR]
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[\fB\-\-context\-length\fR \fILEN\fR]
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[\fB\-\-no\-quant\fR]
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[\fB\-\-outtype\fR \fITYPE\fR]
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[\fB\-\-llama\-cpp\fR \fIPATH\fR]
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[\fB\-\-convert\-to\-quant\fR \fIPATH\fR]
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[\fB\-\-model\-name\fR \fINAME\fR]
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[\fB\-\-device\fR \fIDEVICE\fR]
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[\fB\-\-simple\fR]
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[\fB\-\-optimizer\fR \fIOPT\fR]
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[\fB\-\-num\-iter\fR \fIN\fR]
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[\fB\-\-lr\fR \fILR\fR]
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[\fB\-\-lr\-patience\fR \fIN\fR]
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[\fB\-\-lr\-min\fR \fIMIN\fR]
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[\fB\-\-lr\-schedule\fR \fISCHED\fR]
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[\fB\-\-scale\-optimization\fR \fIMODE\fR]
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[\fB\-\-scale\-refinement\-rounds\fR \fIN\fR]
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[\fB\-\-full\-matrix\fR]
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[\fB\-\-top\-p\fR \fIP\fR]
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[\fB\-\-min\-k\fR \fIK\fR]
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[\fB\-\-max\-k\fR \fIK\fR]
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[\fB\-\-early\-stop\-loss\fR \fILOSS\fR]
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[\fB\-\-early\-stop\-stall\fR \fISTALL\fR]
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[\fB\-\-target\-loss\fR \fITARGET\fR]
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[\fB\-\-early\-stop\-floor\-stall\fR \fIFLOOR\fR]
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[\fB\-\-calib\-samples\fR \fISAMPLES\fR]
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[\fB\-\-seed\fR \fISEED\fR]
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[\fB\-\-no\-bias\-correction\fR]
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[\fB\-\-quantize\-output\fR]
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[\fB\-\-exclude\fR \fIREGEX\fR]
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[\fB\-\-checkpoint\-dir\fR \fIDIR\fR]
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[\fB\-\-fresh\fR]
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[\fB\-\-keep\-checkpoints\fR]
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[\fB\-\-eager\fR]
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[\fB\-\-no\-temp\-file\fR]
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[\fB\-\-verbose\fR]
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[\fB\-\-self\-test\fR]
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[\fB\-h\fR|\fB\-\-help\fR]
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\fImodel\fR
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.SH DESCRIPTION
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.B hf_to_nvfp4_gguf
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quantizes a Hugging Face model directory (\fIconfig.json\fR + safetensors) to
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NVIDIA FP4 (NVFP4) format packaged into a GGUF file suitable for \fBllama.cpp\fR
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and \fBOllama\fR.
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.PP
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The model is loaded through \fBllama.cpp\fR's architecture conversion logic so that
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all vocabulary, tensor naming conventions, tokenization metadata, and architectural
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parameters match native GGUF standards. Weight matrices are quantized using learned
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rounding (via \fBconvert_to_quant\fR) or simple nearest-grid projection onto the E2M1
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floating point grid with two-level scaling (per-block E4M3/E8M0 scales and per-tensor scales).
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.PP
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Along with the output GGUF, an Ollama \fBModelfile\fR is generated automatically,
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preserving the model's chat template, stop sequences, parameter defaults, and vision projectors.
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.SH POSITIONAL ARGUMENTS
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.TP
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.I model
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Path to a Hugging Face model directory containing \fIconfig.json\fR and one or more \fI.safetensors\fR files.
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.SH OPTIONS
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.SS Output & File Control
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.TP
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.BI \-o " " OUTPUT ", " \-\-output " " OUTPUT
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Output destination directory (default: \fI./<model-name>-NVFP4\fR, or \fI./<model-name>\fR with
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\fB\-\-no\-quant\fR and \fBauto\fR). If the path ends in \fI.gguf\fR, it specifies the destination
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GGUF file itself.
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.TP
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.B \-\-overwrite
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Overwrite an existing GGUF, Modelfile, or copied projector without prompting.
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.TP
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.B \-\-modelfile\-only
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Generate only the Ollama \fBModelfile\fR and exit without quantizing or writing GGUF tensors.
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.TP
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.BI \-\-mmproj " " MMPROJ
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Path to a vision projector GGUF. The file is copied into the output directory and added as an
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additional \fBFROM\fR layer in the Modelfile. May be specified multiple times for multimodal models.
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.TP
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.BI \-\-context\-length " " LEN
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Override the maximum context length recorded in the GGUF metadata. Replaces checkpoint value
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or defines one if missing.
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.TP
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.BI \-\-model\-name " " NAME
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Override the model name recorded in the GGUF metadata.
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.SS Quantization Mode
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.TP
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.B \-\-no\-quant
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Skip learned rounding. Writes a float GGUF, or repacks an already NVFP4 checkpoint.
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.TP
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.BI \-\-outtype " " {auto,f32,f16,bf16,nvfp4}
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Data type for non-quantized weights when learned rounding is skipped. \fBnvfp4\fR repacks a
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checkpoint that already has packed 4-bit weights. \fBauto\fR preserves the source float types (default: \fBauto\fR).
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.TP
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.B \-\-simple
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Round weights directly onto the E2M1 grid without iterative learned rounding (fast, non-iterative).
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.TP
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.B \-\-quantize\-output
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Also quantize the final output projection (\fIlm_head\fR) matrix. By default, output layers are
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kept in BF16/float for generation quality.
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.TP
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.BI \-\-exclude " " REGEX
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Regular expression matching GGUF tensor names that should remain unquantized in BF16.
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.SS Optimization & Learned Rounding
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.TP
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.BI \-\-optimizer " " {auto,prodigy,adamw,radam,original}
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Learned-rounding optimization algorithm. \fBauto\fR selects Prodigy if installed, otherwise AdamW (default: \fBauto\fR).
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.TP
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.BI \-\-num\-iter " " N
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Learned-rounding optimization iterations per matrix (default: 4000).
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.TP
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.BI \-\-lr " " LR
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Initial learning rate (default: 1.0).
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.TP
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.BI \-\-lr\-patience " " N
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Number of steps without improvement before decaying the learning rate (default: 5).
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.TP
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.BI \-\-lr\-min " " MIN
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Minimum learning rate floor. The flat-loss termination check begins once this floor is reached (default: 1e-8).
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.TP
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.BI \-\-lr\-schedule " " {plateau,exponential,adaptive}
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Learning rate decay schedule (default: \fBplateau\fR).
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.TP
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.BI \-\-scale\-optimization " " {fixed,iterative,joint}
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Block scale tuning strategy. \fBfixed\fR keeps initial scales; \fBiterative\fR refreshes scales periodically
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using the original optimizer; \fBjoint\fR trains block scales concurrently with the codes (default: \fBjoint\fR).
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.TP
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.BI \-\-scale\-refinement\-rounds " " N
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Number of scale refreshes when \fB\-\-scale\-optimization\fR is set to \fBiterative\fR (default: 2).
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.TP
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.B \-\-full\-matrix
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Use full singular value decomposition (SVD) rather than a low-rank approximation for the loss objective.
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.TP
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.BI \-\-top\-p " " P
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Cumulative energy cutoff for low-rank SVD (default: 0.2).
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.TP
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.BI \-\-min\-k " " K ", " \-\-max\-k " " K
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Minimum and maximum rank limits for low-rank SVD (default: 128 and 1280).
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.TP
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.BI \-\-target\-loss " " TARGET
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Stop optimization when best reconstruction loss reaches this threshold (default: 1e-5; 0 disables).
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.TP
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.BI \-\-early\-stop\-stall " " STALL
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Stop optimization after this many steps without reaching a new best loss (default: 2000).
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.TP
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.BI \-\-early\-stop\-floor\-stall " " FLOOR
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Stop optimization after this many steps without improvement once the learning rate has reached \fB\-\-lr\-min\fR (default: 64; 0 disables).
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.TP
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.BI \-\-calib\-samples " " SAMPLES
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Number of random Gaussian calibration inputs used to calculate sibling bias correction (default: 3072).
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.TP
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.BI \-\-seed " " SEED
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Random seed for calibration vectors (default: 42).
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.TP
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.B \-\-no\-bias\-correction
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Disable sibling bias correction on downstream biases.
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.SS System & Execution
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.TP
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.BI \-\-device " " DEVICE
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Device to perform optimization on: \fBauto\fR, \fBcpu\fR, \fBcuda\fR, or \fBcuda:N\fR (default: \fBauto\fR).
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.TP
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.BI \-\-llama\-cpp " " PATH
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Path to local \fBllama.cpp\fR repository checkout (default: \fI~/llama.cpp\fR).
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.TP
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.BI \-\-convert\-to\-quant " " PATH
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Path to local \fBconvert_to_quant\fR repository checkout, if not installed as a Python package.
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.TP
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.BI \-\-checkpoint\-dir " " DIR
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Directory used to store and resume per-tensor quantization checkpoints.
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.TP
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.B \-\-fresh
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Remove existing checkpoint directory before starting.
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.TP
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.B \-\-keep\-checkpoints
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Preserve per-tensor checkpoints after successful conversion.
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.TP
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.B \-\-eager
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Load all model tensors into memory up front rather than streaming (requires more system RAM).
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.TP
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.B \-\-no\-temp\-file
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Keep finished GGUF tensors in memory rather than buffering through a temporary scratch file.
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.TP
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.B \-\-verbose
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Enable detailed verbose logging.
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.TP
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.B \-\-self\-test
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Run internal verification of NVFP4 packing against llama.cpp's reference dequantizer and exit immediately.
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.SH EXAMPLES
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.TP
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.B Full learned-rounding conversion to GGUF:
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.RS
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.nf
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hf_to_nvfp4_gguf -o ./llama3-8b-NVFP4 ./meta-llama-3-8b
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.fi
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.RE
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.TP
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.B Fast quantization with simple grid rounding:
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.RS
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.nf
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hf_to_nvfp4_gguf --simple -o ./qwen-nvfp4 ./Qwen2.5-7B-Instruct
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.fi
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.RE
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.TP
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.B Multi-modal model with vision projector:
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.RS
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.nf
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hf_to_nvfp4_gguf --mmproj mmproj-model-f16.gguf -o ./vision-nvfp4 ./Qwen2-VL-7B
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.fi
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.RE
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.TP
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.B Specify CUDA GPU and custom llama.cpp directory:
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.RS
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.nf
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hf_to_nvfp4_gguf --llama-cpp /opt/llama.cpp --device cuda:0 -o ./output ./model
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.fi
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.RE
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.SH EXIT STATUS
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.TP
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.B 0
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Success.
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.TP
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.B 1
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An error occurred during conversion or validation.
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.SH SEE ALSO
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.BR gguf_to_nvfp4_gguf (1),
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.BR safetensors_to_nvfp4_gguf (1),
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.BR hf_to_nvfp4_safetensors (1),
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.BR hf_info (1),
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.BR gguf_info (1),
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.BR ollama_nvfp4 (1)
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