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CLI Reference
hk <command> [arguments]
hk helphk is one executable. It needs no Python, no GPU toolkit and no configuration. Commands that take a model accept a .hk file or a Hub reference (owner/name[:quant]); a reference is pulled first if it is not cached yet.
Generates text. Text goes to standard output, statistics to standard error, so the output can be piped.
| Option | Meaning | Default |
|---|---|---|
-p, --prompt TEXT |
text to continue (a bare argument works too; quote it) | none |
--chat |
wrap the prompt as one user message using the model's chat template | off |
-n, --max-tokens N |
most tokens to generate | 128 |
--temp T |
temperature; 0 takes the most likely token |
0.8 |
--top-k N |
keep the N most likely tokens, 0 for no limit |
40 |
--top-p P |
nucleus sampling, 1 disables |
0.95 |
--min-p P |
drop tokens below P times the best one | 0.05 |
--repeat-penalty X |
penalty for recent tokens, 1 disables |
1.0 |
--seed N |
random seed, 0 uses the clock |
0 |
--threads N |
compute threads | physical cores |
-ngl, --gpu-layers N |
run on a GPU (Vulkan) when N > 0; also HK_GPU=1
|
CPU |
Every flag is checked before the model is opened, and an unknown or malformed one is an error, never a silent default. With --temp 0 the output is deterministic.
An interactive session with the model's chat template and history kept across turns. Takes the sampling options of run (not -p or --chat) and -n (default 1024). An empty line ends the session.
An OpenAI compatible HTTP server. See Inference and Serving.
| Command | |
|---|---|
hk pull <owner/name>[:quant] [--force] [--revision REF] |
download and convert, see Downloading Models |
hk search <query> [--limit N] [--all] |
search the Hub |
hk list |
show cached models |
hk rm <owner/name> |
delete a cached model |
hk convert-gguf <in.gguf> <out.hk> |
convert a GGUF file; block formats are carried over byte for byte |
hk convert-safetensors <in.safetensors> <out.hk> [f32|q4_0|q8_0] |
convert one safetensors file, optionally quantizing |
hk export -f gguf <in.hk> <out.gguf> |
write a GGUF v3 file |
hk export -f safetensors <in.hk> <out.safetensors> |
write safetensors; float tensors keep their type, quantized ones are decoded and stored as F16 |
Tensor names are kept as they are in the container, so a model converted from GGUF exports with GGUF names.
| Command | |
|---|---|
hk inspect <file.hk> |
header, metadata and the tensor table |
hk dump <file.hk> |
the header field by field, with offsets |
hk verify <file.hk> |
check the magic, version and the alignment of the payload |
hk hash <file.hk> |
SHA-256 of the container and of every tensor |
hk eval <file.hk> |
parameter count, value range, NaN and Inf count |
hk tokenize <file.hk> "text" |
token ids using the vocabulary stored in the file |
hk detokenize <file.hk> <id> ... |
text from token ids |
hk metadata list <file.hk> / get / set <key> <value>
|
read or change metadata in place; the weights are not rewritten |
hk hardware-profile |
what the processor offers, which kernels are in use, whether a GPU is usable |
hk benchmark <file.hk> |
time to open the file, resolve tensors, touch every page, decode a tensor |
| Command | |
|---|---|
hk expand <in> <out> [--vocab N] [--width R] |
grow the vocabulary and the MLP width of a float model; see Dynamic Architecture Growth |
hk prune <in> <out> [ratio] |
magnitude pruning |
hk retile <in> <out> [tile_16x16|row_major] |
change the layout of 2-D tensors |
hk appendix <file.hk> |
list the version history stored in the file |
hk rollback <file.hk> [generation] |
cut the version history back; this truncates the file |
hk convert-endian <in> <out> |
byte swap a container |
hk gui [file.hk] |
the Tk model editor (needs Python and Tk) |
hk expand refuses quantized models, and says so when no tensor name matched (it looks for Hugging Face style names).
| Variable | Effect |
|---|---|
HK_HOME |
model cache directory |
HF_TOKEN, HF_ENDPOINT, HK_HTTP_BACKOFF_MS
|
downloads, see Downloading Models |
HK_GPU=1 |
use the GPU when possible, without -ngl
|
HK_KERNELS=<level> |
force an instruction set level (for example avx2 or generic); useful for testing and measuring |
HK_THREADS=N |
thread count for the developer tools |
HK_API_KEY |
API key for hk serve
|
Zero on success, non-zero on any error. Messages for the user go to standard error.
HK Neural Tensor Framework | Licensed under Apache 2.0 | GitHub Repository