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Split Kimodo GGML distributions

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This commit is contained in:
Richard Palethorpe 2026-08-23 14:46:48 +01:00
parent e3eb09fec6
commit ac35407fc0
9 changed files with 191 additions and 126 deletions
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17
README.md
View File

@ -63,15 +63,18 @@ new generation.
## Weights
The ready-to-run native GGUF bundle is published under the Hugging Face
`LocalAI-io` organisation (not GitHub's `localai-org`). Download it directly;
this avoids recreating the conversion locally:
Ready-to-run native GGML weights are published under the Hugging Face
`LocalAI-io` organisation (not GitHub's `localai-org`). The reusable
[Llama-3-Kimodo-GGML](https://huggingface.co/LocalAI-io/Llama-3-Kimodo-GGML)
text encoder and the upstream-linked
[Kimodo-SMPLX-RP-v1-GGML](https://huggingface.co/LocalAI-io/Kimodo-SMPLX-RP-v1-GGML)
diffusion model are separate, so users download rather than recreate them:
```sh
nix develop path:. --command scripts/download_gguf_weights.sh --output "$PWD"
```
The installer verifies the published manifest and SHA-256 hashes. Use
The installer verifies each published manifest and SHA-256 hashes. Use
`--motion-only` when supplying a precomputed 4096-float LLM2Vec embedding.
The GGUF bundle includes converted Meta Llama 3 material and Kimodo is
@ -101,7 +104,9 @@ Validate a prospective release without network access, then explicitly upload
it from an account allowed to publish to `LocalAI-io`:
```sh
nix develop path:. --command python scripts/publish_gguf.py
nix develop path:. --command python scripts/publish_gguf.py \
nix develop path:. --command python scripts/publish_gguf.py --component motion
nix develop path:. --command python scripts/publish_gguf.py --component motion \
--upload --confirm-upstream-licences
nix develop path:. --command python scripts/publish_gguf.py --component text \
--upload --confirm-upstream-licences
```

55
demo/main.go
View File

@ -36,6 +36,16 @@ type animation struct {
Status string `json:"status"`
Error string `json:"error,omitempty"`
Kind string `json:"kind"`
Model string `json:"model"`
}
type motionModel struct {
ID string `json:"id"`
Label string `json:"label"`
Skeleton string `json:"skeleton"`
Upstream string `json:"upstream"`
Available bool `json:"available"`
Reason string `json:"reason,omitempty"`
Motion string `json:"-"`
}
type gallery struct {
mu sync.RWMutex
@ -43,6 +53,7 @@ type gallery struct {
output string
queue chan string
generator, motion, text string
models map[string]motionModel
}
func token() string {
@ -83,11 +94,16 @@ func (g *gallery) worker() {
err = os.WriteFile(filepath.Join(dir, "prompt.txt"), []byte(item.Prompt), 0600)
}
if err == nil {
cmd := exec.Command(g.generator, g.motion, g.text, filepath.Join(dir, "prompt.txt"), fmt.Sprint(item.Frames), fmt.Sprint(item.DiffusionSteps), fmt.Sprint(item.Seed), dir)
cmd.Env = append(os.Environ(), "KIMODO_BACKEND=vulkan")
output, runErr := cmd.CombinedOutput()
if runErr != nil {
err = fmt.Errorf("%w: %s", runErr, strings.TrimSpace(string(output)))
model, ok := g.models[item.Model]
if !ok || !model.Available {
err = fmt.Errorf("model %q is not available", item.Model)
} else {
cmd := exec.Command(g.generator, model.Motion, g.text, filepath.Join(dir, "prompt.txt"), fmt.Sprint(item.Frames), fmt.Sprint(item.DiffusionSteps), fmt.Sprint(item.Seed), dir)
cmd.Env = append(os.Environ(), "KIMODO_BACKEND=vulkan")
output, runErr := cmd.CombinedOutput()
if runErr != nil {
err = fmt.Errorf("%w: %s", runErr, strings.TrimSpace(string(output)))
}
}
}
g.mu.Lock()
@ -114,7 +130,14 @@ func main() {
if err := os.MkdirAll(*output, 0755); err != nil {
log.Fatal(err)
}
g := &gallery{items: map[string]*animation{}, output: *output, queue: make(chan string, 32), generator: *generator, motion: *motion, text: *text}
models := map[string]motionModel{
"smplx-rp-v1": {ID: "smplx-rp-v1", Label: "SMPL-X RP v1", Skeleton: "SMPL-X 22 joints", Upstream: "nvidia/Kimodo-SMPLX-RP-v1", Available: true, Motion: *motion},
"soma-rp-v1.1": {ID: "soma-rp-v1.1", Label: "SOMA RP v1.1", Skeleton: "SOMA 30 joints", Upstream: "nvidia/Kimodo-SOMA-RP-v1.1", Reason: "SOMA decoder and GGML conversion are being added"},
"soma-seed-v1.1": {ID: "soma-seed-v1.1", Label: "SOMA SEED v1.1", Skeleton: "SOMA 30 joints", Upstream: "nvidia/Kimodo-SOMA-SEED-v1.1", Reason: "SOMA decoder and GGML conversion are being added"},
"g1-rp-v1": {ID: "g1-rp-v1", Label: "G1 RP v1", Skeleton: "Unitree G1 34 joints", Upstream: "nvidia/Kimodo-G1-RP-v1", Reason: "G1 decoder and GGML conversion are being added"},
"g1-seed-v1": {ID: "g1-seed-v1", Label: "G1 SEED v1", Skeleton: "Unitree G1 34 joints", Upstream: "nvidia/Kimodo-G1-SEED-v1", Reason: "G1 decoder and GGML conversion are being added"},
}
g := &gallery{items: map[string]*animation{}, output: *output, queue: make(chan string, 32), generator: *generator, motion: *motion, text: *text, models: models}
entries, _ := filepath.Glob(filepath.Join(*output, "*.json"))
for _, path := range entries {
b, err := os.ReadFile(path)
@ -149,6 +172,15 @@ func main() {
w.Header().Set("Content-Type", "application/json")
_ = json.NewEncoder(w).Encode(g.list())
})
mux.HandleFunc("/api/models", func(w http.ResponseWriter, r *http.Request) {
result := make([]motionModel, 0, len(g.models))
for _, model := range g.models {
result = append(result, model)
}
sort.Slice(result, func(i, j int) bool { return result[i].ID < result[j].ID })
w.Header().Set("Content-Type", "application/json")
_ = json.NewEncoder(w).Encode(result)
})
mux.HandleFunc("/api/generate", func(w http.ResponseWriter, r *http.Request) {
if r.Method != http.MethodPost {
w.Header().Set("Allow", http.MethodPost)
@ -160,6 +192,7 @@ func main() {
Frames int `json:"frames"`
Steps int `json:"steps"`
Seed uint64 `json:"seed"`
Model string `json:"model"`
}
if err := json.NewDecoder(http.MaxBytesReader(w, r.Body, 32<<10)).Decode(&request); err != nil {
http.Error(w, "invalid JSON", 400)
@ -180,7 +213,15 @@ func main() {
http.Error(w, "frames and steps must be 1..1000", 400)
return
}
a := &animation{ID: token(), Prompt: request.Prompt, Frames: request.Frames, DiffusionSteps: request.Steps, Seed: request.Seed, CreatedAt: time.Now().UTC().Format(time.RFC3339), Status: "queued", Kind: "generated"}
if request.Model == "" {
request.Model = "smplx-rp-v1"
}
model, ok := g.models[request.Model]
if !ok || !model.Available {
http.Error(w, "selected motion model is not available: "+model.Reason, http.StatusConflict)
return
}
a := &animation{ID: token(), Prompt: request.Prompt, Frames: request.Frames, DiffusionSteps: request.Steps, Seed: request.Seed, CreatedAt: time.Now().UTC().Format(time.RFC3339), Status: "queued", Kind: "generated", Model: request.Model}
g.mu.Lock()
g.items[a.ID] = a
err := g.save(a)

42
scripts/download_gguf_weights.sh
View File

@ -4,18 +4,20 @@ set -euo pipefail
export HF_HUB_DISABLE_PROGRESS_BARS=1
ORG="${GGUF_ORG:-LocalAI-io}"
REPO_DEFAULT="$ORG/Llama-3-Kimodo-SMPLX-RP-v1-GGUF"
MOTION_REPO_DEFAULT="$ORG/Kimodo-SMPLX-RP-v1-GGML"
TEXT_REPO_DEFAULT="$ORG/Llama-3-Kimodo-GGML"
usage() {
printf '%s\n' "usage: $0 --output DIR [--repo HF_REPO] [--revision REVISION] [--motion-only]" >&2
printf '%s\n' "usage: $0 --output DIR [--motion-repo HF_REPO] [--text-repo HF_REPO] [--revision REVISION] [--motion-only]" >&2
exit 2
}
output='' repo="$REPO_DEFAULT" revision='main' motion_only=0
output='' motion_repo="$MOTION_REPO_DEFAULT" text_repo="$TEXT_REPO_DEFAULT" revision='main' motion_only=0
while [ "$#" -gt 0 ]; do
case "$1" in
--output) [ "$#" -ge 2 ] || usage; output=$2; shift 2 ;;
--repo) [ "$#" -ge 2 ] || usage; repo=$2; shift 2 ;;
--motion-repo) [ "$#" -ge 2 ] || usage; motion_repo=$2; shift 2 ;;
--text-repo) [ "$#" -ge 2 ] || usage; text_repo=$2; shift 2 ;;
--revision) [ "$#" -ge 2 ] || usage; revision=$2; shift 2 ;;
--motion-only) motion_only=1; shift ;;
*) usage ;;
@ -25,18 +27,18 @@ done
command -v hf >/dev/null || { echo "hf not found; enter the Nix shell first" >&2; exit 1; }
mkdir -p "$output"
patterns=("MANIFEST.json" "SHA256SUMS" "models/kimodo-smplx-rp-v1-f32.gguf")
if [ "$motion_only" -eq 0 ]; then
patterns+=("generated/llm2vec-text-bundle/*")
fi
echo "Downloading $repo at $revision into $output"
args=(download "$repo" --revision "$revision" --local-dir "$output")
for pattern in "${patterns[@]}"; do args+=(--include "$pattern"); done
hf "${args[@]}" >/dev/null
manifest="$output/MANIFEST.json"
[ -f "$manifest" ] || { echo "missing MANIFEST.json from $repo" >&2; exit 1; }
python - "$manifest" "$output" "$motion_only" <<'PY'
download_and_verify() { # repo include-pattern...
local repo=$1; shift
local manifest_dir="$output/.kimodo-manifests/${repo//\//__}"
mkdir -p "$manifest_dir"
echo "Downloading $repo at $revision into $output"
local args=(download "$repo" --revision "$revision" --local-dir "$output")
local pattern
for pattern in "$@"; do args+=(--include "$pattern"); done
hf "${args[@]}" >/dev/null
hf download "$repo" --revision "$revision" --local-dir "$manifest_dir" --include MANIFEST.json >/dev/null
python - "$manifest_dir/MANIFEST.json" "$output" "$@" <<'PY'
import hashlib
import json
import sys
@ -44,16 +46,16 @@ from pathlib import Path
manifest_path = Path(sys.argv[1])
output = Path(sys.argv[2])
motion_only = sys.argv[3] == "1"
root = output.resolve()
manifest = json.loads(manifest_path.read_text(encoding="utf-8"))
if manifest.get("format") != "kimodo-gguf-manifest-v1":
raise SystemExit("unsupported or malformed GGUF manifest")
requested = sys.argv[3:]
for entry in manifest.get("files", []):
relative = Path(entry.get("path", ""))
if relative.is_absolute() or ".." in relative.parts or relative.suffix != ".gguf":
raise SystemExit(f"unsafe manifest path: {relative}")
if motion_only and str(relative).startswith("generated/"):
if not any(relative.match(pattern) for pattern in requested):
continue
path = root / relative
if not path.is_file() or path.stat().st_size != entry.get("bytes"):
@ -66,3 +68,9 @@ for entry in manifest.get("files", []):
raise SystemExit(f"checksum mismatch: {relative}")
print("verified native Kimodo GGUF bundle")
PY
}
download_and_verify "$motion_repo" "models/kimodo-smplx-rp-v1-f32.gguf"
if [ "$motion_only" -eq 0 ]; then
download_and_verify "$text_repo" "generated/llm2vec-text-bundle/*"
fi

4
scripts/hf/Llama-3-Kimodo-SMPLX-RP-v1-GGUF/NOTICE → scripts/hf/Kimodo-SMPLX-RP-v1-GGML/NOTICE
View File

@ -1,7 +1,3 @@
Meta Llama 3 is licensed under the Meta Llama 3 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.
Built with Meta Llama 3.
Kimodo-SMPLX-RP-v1 source model: NVIDIA. This converted distribution remains
subject to the NVIDIA Internal Scientific Research and Development Model License
and is for non-commercial research use only.

33
scripts/hf/Kimodo-SMPLX-RP-v1-GGML/README.md Normal file
View File

@ -0,0 +1,33 @@
---
license: other
library_name: ggml
tags: [gguf, ggml, text-to-motion, smplx, kimodo]
---
# Kimodo-SMPLX-RP-v1-GGML
Native F32 GGML/GGUF conversion of
[nvidia/Kimodo-SMPLX-RP-v1](https://huggingface.co/nvidia/Kimodo-SMPLX-RP-v1),
the SMPL-X 22-joint text-and-constraint conditioned motion diffusion model.
This repository contains only the diffusion model; its reusable Llama-derived
text encoder is distributed separately as
[`Llama-3-Kimodo-GGML`](https://huggingface.co/LocalAI-io/Llama-3-Kimodo-GGML).
From a kimodo.cpp checkout, install both with:
```sh
nix develop path:. --command scripts/download_gguf_weights.sh --output "$PWD"
```
The model is installed at `models/kimodo-smplx-rp-v1-f32.gguf`. Use
`--motion-only` when supplying a precomputed LLM2Vec embedding.
## Provenance and licence
Converted by kimodo.cpp from upstream commit
`1419ba56b734c48bbafb41fefa84088ca94583b5`. `MANIFEST.json` records the
source revision and SHA-256 of the GGUF.
Kimodo-SMPLX-RP-v1 is for non-commercial research use only and remains subject
to the [NVIDIA Internal Scientific Research and Development Model License](https://huggingface.co/nvidia/Kimodo-SMPLX-RP-v1).
This conversion grants no additional rights.

3
scripts/hf/Llama-3-Kimodo-GGML/NOTICE Normal file
View File

@ -0,0 +1,3 @@
Meta Llama 3 is licensed under the Meta Llama 3 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.
Built with Meta Llama 3.

31
scripts/hf/Llama-3-Kimodo-GGML/README.md Normal file
View File

@ -0,0 +1,31 @@
---
license: other
library_name: ggml
tags: [gguf, ggml, llama-3, text-embeddings]
---
# Llama-3-Kimodo-GGML
Native F32 GGML/GGUF text-encoder components used by Kimodo. This is the
reusable LLM2Vec encoder only; download a matching Kimodo diffusion model
separately, for example
[`Kimodo-SMPLX-RP-v1-GGML`](https://huggingface.co/LocalAI-io/Kimodo-SMPLX-RP-v1-GGML).
From a kimodo.cpp checkout, install both with:
```sh
nix develop path:. --command scripts/download_gguf_weights.sh --output "$PWD"
```
The components intentionally remain split into individual layers so kimodo.cpp
can bound GPU memory use while evaluating the encoder.
## Provenance and licence
The bundle is converted from Meta Llama-3-8B-Instruct and the MIT-licensed
McGill LLM2Vec MNTP and supervised adapters. **Built with Meta Llama 3.**
`LICENSE-META-LLAMA-3.txt` and `NOTICE` accompany this distribution. Review
the [Meta Llama 3 Community License](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)
before use or redistribution. `MANIFEST.json` records the exact source commits
and SHA-256 of each component.

66
scripts/hf/Llama-3-Kimodo-SMPLX-RP-v1-GGUF/README.md
View File

@ -1,66 +0,0 @@
---
license: other
library_name: ggml
tags:
- gguf
- ggml
- text-to-motion
- smplx
- llama-3
---
# Llama-3-Kimodo-SMPLX-RP-v1-GGUF
Native F32 GGUF conversion of NVIDIA's Kimodo-SMPLX-RP-v1 motion model and
its LLM2Vec text encoder. It is for the `kimodo.cpp` GGML runtime; it is not a
llama.cpp language-model conversion.
`Kimodo-SMPLX-RP-v1` is restricted to non-commercial research use. Before use
or redistribution, review and comply with the upstream NVIDIA model terms and
the Meta Llama 3 Community License below. This repository does not grant rights
beyond those upstream licences.
## Install
From the kimodo.cpp checkout:
```sh
nix develop path:. --command scripts/download_gguf_weights.sh --output "$PWD"
```
This places the motion model at `models/kimodo-smplx-rp-v1-f32.gguf` and text
components under `generated/llm2vec-text-bundle/`, which are the default paths
used by the library and demo. Add `--motion-only` for embedding-only inference.
`SHA256SUMS` and `MANIFEST.json` record every published artifact and its source
revision; the installer verifies the selected files after download.
## Contents
- `models/kimodo-smplx-rp-v1-f32.gguf` — Kimodo motion diffusion model (F32)
- `generated/llm2vec-text-bundle/` — tokenizer, embeddings, final norm, and 32
F32 transformer layers for native LLM2Vec inference
The text components are split deliberately: kimodo.cpp loads a bounded number
of layers at once for GPU memory control.
## Provenance
The conversion is generated by `kimodo.cpp` from these exact upstream commits:
- NVIDIA Kimodo-SMPLX-RP-v1: `1419ba56b734c48bbafb41fefa84088ca94583b5`
- Meta Llama-3-8B-Instruct: `8afb486c1db24fe5011ec46dfbe5b5dccdb575c2`
- McGill LLM2Vec MNTP adapter: `31474e395ada192e8ed1586db6be79fb3b70c9c0`
- McGill LLM2Vec supervised adapter: `baa8ebf04a1c2500e61288e7dad65e8ae42601a7`
The two McGill adapters are MIT-licensed. The merged text encoder includes
Meta Llama 3 material. **Built with Meta Llama 3.**
## Licences and notices
- Kimodo: [NVIDIA Internal Scientific Research and Development Model License](https://huggingface.co/nvidia/Kimodo-SMPLX-RP-v1)
(non-commercial research only).
- Text base: [Meta Llama 3 Community License](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct).
- LLM2Vec adapters: [MIT](https://huggingface.co/McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp).
`LICENSE-META-LLAMA-3.txt` and `NOTICE` accompany every published copy with
the required Meta licence and attribution.

66
scripts/publish_gguf.py
View File

@ -5,11 +5,9 @@ The default is deliberately a dry run: it validates the exact converter
outputs, prints every path, size and SHA-256, and performs no network I/O.
Use --upload only after reviewing the upstream licence obligations.
The text bundle contains merged Meta Llama 3 weights. It is therefore kept in
the same repository as the Kimodo motion GGUF and is published under the model
name required by the Meta Llama 3 Community License:
LocalAI-io/Llama-3-Kimodo-SMPLX-RP-v1-GGUF
The text bundle contains merged Meta Llama 3 weights and is published separately
from the Kimodo motion model, so the latter keeps a direct relationship to its
upstream NVIDIA model repository.
"""
from __future__ import annotations
@ -23,7 +21,10 @@ from pathlib import Path
ROOT = Path(__file__).resolve().parent.parent
HF_ORG = "LocalAI-io" # Hugging Face organisation; GitHub is localai-org.
DEFAULT_REPO = f"{HF_ORG}/Llama-3-Kimodo-SMPLX-RP-v1-GGUF"
DEFAULT_REPOS = {
"text": f"{HF_ORG}/Llama-3-Kimodo-GGML",
"motion": f"{HF_ORG}/Kimodo-SMPLX-RP-v1-GGML",
}
MOTION_NAME = "kimodo-smplx-rp-v1-f32.gguf"
TEXT_NAMES = (
"tokenizer.gguf", "embedding.gguf", "final-norm.gguf",
@ -35,8 +36,6 @@ SOURCE_REVISIONS = {
"McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp": "31474e395ada192e8ed1586db6be79fb3b70c9c0",
"McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp-supervised": "baa8ebf04a1c2500e61288e7dad65e8ae42601a7",
}
CARD = ROOT / "scripts/hf/Llama-3-Kimodo-SMPLX-RP-v1-GGUF/README.md"
NOTICE = ROOT / "scripts/hf/Llama-3-Kimodo-SMPLX-RP-v1-GGUF/NOTICE"
LLAMA_LICENSE = ROOT / "models/llama3-8b-instruct-base/LICENSE"
@ -62,9 +61,12 @@ def require_revision(repo: str) -> None:
raise ValueError(f"unexpected {repo} revision: {actual} (expected {SOURCE_REVISIONS[repo]})")
def artifacts(motion: Path, bundle: Path) -> list[tuple[Path, str]]:
result = [(motion, f"models/{MOTION_NAME}")]
result.extend((bundle / name, f"generated/llm2vec-text-bundle/{name}") for name in TEXT_NAMES)
def artifacts(component: str, motion: Path, bundle: Path) -> list[tuple[Path, str]]:
result: list[tuple[Path, str]] = []
if component == "motion":
result.append((motion, f"models/{MOTION_NAME}"))
else:
result.extend((bundle / name, f"generated/llm2vec-text-bundle/{name}") for name in TEXT_NAMES)
for source, destination in result:
if not source.is_file() or source.stat().st_size == 0:
raise ValueError(f"missing or empty GGUF: {source}")
@ -83,19 +85,29 @@ def main() -> int:
parser.add_argument("--motion", type=Path, default=ROOT / "models" / MOTION_NAME)
parser.add_argument("--text-bundle", type=Path,
default=ROOT / "generated/llm2vec-text-bundle")
parser.add_argument("--repo", default=DEFAULT_REPO)
parser.add_argument("--component", choices=("text", "motion"), required=True,
help="which independently licensed distribution to publish")
parser.add_argument("--repo", default=None, help="override the component's HF repository")
parser.add_argument("--upload", action="store_true",
help="actually create/update the Hugging Face model repo")
parser.add_argument("--confirm-upstream-licences", action="store_true",
help="required with --upload; confirms authority to redistribute all inputs")
args = parser.parse_args()
repo = args.repo or DEFAULT_REPOS[args.component]
card_dir = ROOT / "scripts/hf" / ("Llama-3-Kimodo-GGML" if args.component == "text" else "Kimodo-SMPLX-RP-v1-GGML")
card = card_dir / "README.md"
notice = card_dir / "NOTICE"
relevant_sources = (SOURCE_REVISIONS if args.component == "text"
else {"nvidia/Kimodo-SMPLX-RP-v1": SOURCE_REVISIONS["nvidia/Kimodo-SMPLX-RP-v1"]})
try:
if not CARD.is_file() or not NOTICE.is_file() or not LLAMA_LICENSE.is_file():
raise ValueError("model card, NOTICE, or Meta Llama 3 licence is missing")
for repo in SOURCE_REVISIONS:
require_revision(repo)
files = artifacts(args.motion, args.text_bundle)
if not card.is_file() or not notice.is_file():
raise ValueError("version-controlled model card or NOTICE is missing")
if args.component == "text" and not LLAMA_LICENSE.is_file():
raise ValueError("Meta Llama 3 licence is missing")
for source_repo in relevant_sources:
require_revision(source_repo)
files = artifacts(args.component, args.motion, args.text_bundle)
except ValueError as error:
print(f"error: {error}", file=sys.stderr)
return 1
@ -105,14 +117,15 @@ def main() -> int:
entries.append({"path": destination, "bytes": source.stat().st_size, "sha256": digest(source)})
manifest = {
"format": "kimodo-gguf-manifest-v1",
"repository": args.repo,
"source_revisions": SOURCE_REVISIONS,
"repository": repo,
"component": args.component,
"source_revisions": relevant_sources,
"files": entries,
}
sums = "".join(f"{entry['sha256']} {entry['path']}\n" for entry in entries)
total = sum(entry["bytes"] for entry in entries)
print(f"repo: https://huggingface.co/{args.repo}")
print(f"repo: https://huggingface.co/{repo}")
print(f"files: {len(entries)} GGUFs, {total / 1e9:.2f} GB")
for entry in entries:
print(f" {entry['sha256']} {entry['bytes']:>12} {entry['path']}")
@ -125,21 +138,22 @@ def main() -> int:
from huggingface_hub import HfApi
api = HfApi()
api.create_repo(args.repo, repo_type="model", exist_ok=True)
uploads = [(CARD, "README.md"), (NOTICE, "NOTICE"),
(LLAMA_LICENSE, "LICENSE-META-LLAMA-3.txt")]
api.create_repo(repo, repo_type="model", exist_ok=True)
uploads = [(card, "README.md"), (notice, "NOTICE")]
if args.component == "text":
uploads.append((LLAMA_LICENSE, "LICENSE-META-LLAMA-3.txt"))
for source, destination in uploads + files:
print(f"uploading {destination} ...", flush=True)
api.upload_file(path_or_fileobj=str(source), path_in_repo=destination,
repo_id=args.repo, repo_type="model",
repo_id=repo, repo_type="model",
commit_message=f"Add {destination}")
for payload, destination in ((json.dumps(manifest, indent=2, sort_keys=True).encode() + b"\n", "MANIFEST.json"),
(sums.encode(), "SHA256SUMS")):
print(f"uploading {destination} ...", flush=True)
api.upload_file(path_or_fileobj=io.BytesIO(payload), path_in_repo=destination,
repo_id=args.repo, repo_type="model",
repo_id=repo, repo_type="model",
commit_message=f"Add {destination}")
print(f"done -> https://huggingface.co/{args.repo}")
print(f"done -> https://huggingface.co/{repo}")
return 0