Instructions to use eyad-silx/progress with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use eyad-silx/progress with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf eyad-silx/progress # Run inference directly in the terminal: llama cli -hf eyad-silx/progress
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf eyad-silx/progress # Run inference directly in the terminal: llama cli -hf eyad-silx/progress
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf eyad-silx/progress # Run inference directly in the terminal: ./build/bin/llama cli -hf eyad-silx/progress
Use Docker
docker model run hf.co/eyad-silx/progress
- Llama new
- LM Studio
- Jan
- Ollama
How to use eyad-silx/progress with Ollama:
ollama run hf.co/eyad-silx/progress
- Unsloth Desktop
- Pi
How to use eyad-silx/progress with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf eyad-silx/progress
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "eyad-silx/progress" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use eyad-silx/progress with Docker Model Runner:
docker model run hf.co/eyad-silx/progress
- Lemonade
How to use eyad-silx/progress with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull eyad-silx/progress
Run and chat with the model
lemonade run user.progress-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use eyad-silx/progress with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf eyad-silx/progress
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default eyad-silx/progress
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use eyad-silx/progress with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf eyad-silx/progress
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "eyad-silx/progress" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
push artifacts/scripts/hf_push.py
Browse files- artifacts/scripts/hf_push.py +152 -0
artifacts/scripts/hf_push.py
ADDED
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@@ -0,0 +1,152 @@
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| 1 |
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#!/usr/bin/env python3
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| 2 |
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"""Push Ingot (SN97) build-pod artifacts to HF repo eyad-silx/progress.
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| 3 |
+
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| 4 |
+
Modes: --small (docs/logs/scripts), --big (GGUFs + QAT states), default = both.
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| 5 |
+
Only uploads new/changed files (size+mtime_ns fingerprint), records sha256 in
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| 6 |
+
state for the MANIFEST. State: /root/.hf_push_state.json. Log: /root/hf_push.log.
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| 7 |
+
"""
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| 8 |
+
import argparse, glob, hashlib, json, os, sys
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| 9 |
+
from datetime import datetime, timezone
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| 10 |
+
from pathlib import Path
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| 11 |
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from huggingface_hub import HfApi
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| 12 |
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| 13 |
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REPO = "eyad-silx/progress"
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| 14 |
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TOKEN = Path("/root/.hf_token").read_text().strip()
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| 15 |
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STATE_P = Path("/root/.hf_push_state.json")
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| 16 |
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LOG_P = Path("/root/hf_push.log")
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| 17 |
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| 18 |
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README = """# Ingot (SN97) challenger build β progress proof
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| 19 |
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| 20 |
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Automated backup of build/train/eval artifacts from the H100 pod (RunPod, 1x H100 NVL).
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| 21 |
+
Pushed by `hf_push.py` β checks hourly and uploads any new/changed artifact.
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| 22 |
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| 23 |
+
- `king-ix/` β incumbent king GGUF (Ingot-IX-27B-Q2) + provenance files (baseline)
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| 24 |
+
- `chal-identity/`, `chal-v1/`, `chal-n2/`, `chal-norms/` β challenger GGUF iterations
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| 25 |
+
(scale-refit / QAT variants; same 27B Q2 architecture as the king)
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| 26 |
+
- `states/` β QAT state checkpoints (`t0..tN.safetensors`)
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| 27 |
+
- `artifacts/` β `HANDOFF.md`, build/train/eval scripts, run logs, sample draws,
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| 28 |
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measurement results (`measure*.jsonl`, `pick*.jsonl`, `drawn.jsonl`)
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| 29 |
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- `MANIFEST.md` β size + sha256 + upload time of every artifact (regenerated each push)
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| 30 |
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- `PROGRESS.md` β push history
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| 31 |
+
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| 32 |
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The GGUFs are ~6.8 GB each (PQ2_0 quantized 27B linear-attention models).
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| 33 |
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"""
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| 34 |
+
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| 35 |
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def now():
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| 36 |
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return datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
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| 37 |
+
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| 38 |
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def log(evt, **kw):
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| 39 |
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line = json.dumps({"t": now(), "event": evt, **kw})
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| 40 |
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with open(LOG_P, "a") as f:
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| 41 |
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f.write(line + "\n")
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| 42 |
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print(line, flush=True)
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| 43 |
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| 44 |
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def sha256(p):
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| 45 |
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h = hashlib.sha256()
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| 46 |
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with open(p, "rb") as f:
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| 47 |
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for chunk in iter(lambda: f.read(1 << 24), b""):
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| 48 |
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h.update(chunk)
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| 49 |
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return h.hexdigest()
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| 50 |
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| 51 |
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def load_state():
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| 52 |
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return json.loads(STATE_P.read_text()) if STATE_P.exists() else {}
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| 53 |
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| 54 |
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def save_state(s):
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| 55 |
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STATE_P.write_text(json.dumps(s, indent=1, sort_keys=True))
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| 56 |
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| 57 |
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def small_tracks():
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| 58 |
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t = [("/root/HANDOFF.md", "artifacts/HANDOFF.md")]
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| 59 |
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for pat, dest in [("/root/*.py", "artifacts/scripts/"),
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("/root/*.sh", "artifacts/scripts/"),
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| 61 |
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("/root/*.jsonl", "artifacts/"),
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| 62 |
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("/root/*.json", "artifacts/"),
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| 63 |
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("/root/*.log", "artifacts/logs/")]:
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| 64 |
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for p in sorted(glob.glob(pat)):
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| 65 |
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name = os.path.basename(p)
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| 66 |
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if name in ("hf_push.log", "hf_push_nohup.log"):
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| 67 |
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continue
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| 68 |
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t.append((p, dest + name))
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| 69 |
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for extra in ("README.md", "LICENSE", "NOTICE.txt"):
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| 70 |
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p = f"/root/models/king-ix/{extra}"
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| 71 |
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if os.path.exists(p):
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| 72 |
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t.append((p, f"king-ix/{extra}"))
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| 73 |
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return t
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| 74 |
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| 75 |
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def big_tracks():
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| 76 |
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# priority order: newest challenger first (pod lifetime is uncertain)
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| 77 |
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t = [("/root/models/chal-identity/Ingot-IX-27B-Q2.gguf", "chal-identity/Ingot-IX-27B-Q2.gguf"),
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| 78 |
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("/root/models/chal-v1/chal-v1.gguf", "chal-v1/chal-v1.gguf"),
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| 79 |
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("/root/models/chal-n2/chal-norms.gguf", "chal-n2/chal-norms.gguf"),
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| 80 |
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("/root/models/chal-norms/chal-norms.gguf", "chal-norms/chal-norms.gguf"),
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| 81 |
+
("/root/models/king-ix/Ingot-IX-27B-Q2.gguf", "king-ix/Ingot-IX-27B-Q2.gguf")]
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| 82 |
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for p in sorted(glob.glob("/root/states/*.safetensors")):
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| 83 |
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t.append((p, "states/" + os.path.basename(p)))
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| 84 |
+
return t
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| 85 |
+
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| 86 |
+
def main():
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| 87 |
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ap = argparse.ArgumentParser()
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| 88 |
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ap.add_argument("--small", action="store_true")
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| 89 |
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ap.add_argument("--big", action="store_true")
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| 90 |
+
args = ap.parse_args()
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| 91 |
+
if args.small or args.big:
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| 92 |
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tracks = (small_tracks() if args.small else []) + (big_tracks() if args.big else [])
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| 93 |
+
else:
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| 94 |
+
tracks = small_tracks() + big_tracks()
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| 95 |
+
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| 96 |
+
state = load_state()
|
| 97 |
+
api = HfApi(token=TOKEN)
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| 98 |
+
results = []
|
| 99 |
+
for local, repo in tracks:
|
| 100 |
+
if not os.path.exists(local):
|
| 101 |
+
continue
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| 102 |
+
st = os.stat(local)
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| 103 |
+
fp = f"{st.st_size}:{st.st_mtime_ns}"
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| 104 |
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prev = state.get(repo)
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| 105 |
+
if prev and prev["fp"] == fp:
|
| 106 |
+
results.append((repo, "unchanged"))
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| 107 |
+
continue
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| 108 |
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try:
|
| 109 |
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d = sha256(local)
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| 110 |
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api.upload_file(path_or_fileobj=local, path_in_repo=repo, repo_id=REPO,
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| 111 |
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repo_type="model", commit_message=f"push {repo}")
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| 112 |
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state[repo] = {"fp": fp, "sha256": d, "size": st.st_size, "uploaded_at": now()}
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| 113 |
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save_state(state)
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| 114 |
+
log("uploaded", local=local, repo=repo, sha256=d, size=st.st_size)
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| 115 |
+
results.append((repo, "uploaded"))
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| 116 |
+
except Exception as e:
|
| 117 |
+
log("error", local=local, repo=repo, err=repr(e)[:500])
|
| 118 |
+
results.append((repo, "FAILED"))
|
| 119 |
+
|
| 120 |
+
# regenerate docs (manifest / progress / readme) from state
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| 121 |
+
try:
|
| 122 |
+
manifest = ["# Manifest β eyad-silx/progress", "",
|
| 123 |
+
"| repo path | size (bytes) | sha256 | uploaded (UTC) |",
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| 124 |
+
"|---|---|---|---|"]
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| 125 |
+
for repo in sorted(state):
|
| 126 |
+
v = state[repo]
|
| 127 |
+
manifest.append(f"| `{repo}` | {v['size']:,} | `{v['sha256']}` | {v['uploaded_at']} |")
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| 128 |
+
Path("/tmp/MANIFEST.md").write_text("\n".join(manifest) + "\n")
|
| 129 |
+
api.upload_file(path_or_fileobj="/tmp/MANIFEST.md", path_in_repo="MANIFEST.md",
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| 130 |
+
repo_id=REPO, repo_type="model", commit_message="update MANIFEST.md")
|
| 131 |
+
|
| 132 |
+
hist = [json.loads(l) for l in LOG_P.read_text().splitlines()[-80:] if l.strip()]
|
| 133 |
+
prog = ["# Progress β push history", "", f"Last run: {now()}", ""]
|
| 134 |
+
prog += [f"- `{h['t']}` **{h['event']}** {h.get('repo', h.get('local', ''))}" for h in hist]
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| 135 |
+
Path("/tmp/PROGRESS.md").write_text("\n".join(prog) + "\n")
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| 136 |
+
api.upload_file(path_or_fileobj="/tmp/PROGRESS.md", path_in_repo="PROGRESS.md",
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| 137 |
+
repo_id=REPO, repo_type="model", commit_message="update PROGRESS.md")
|
| 138 |
+
|
| 139 |
+
Path("/tmp/README_REPO.md").write_text(README)
|
| 140 |
+
api.upload_file(path_or_fileobj="/tmp/README_REPO.md", path_in_repo="README.md",
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| 141 |
+
repo_id=REPO, repo_type="model", commit_message="README")
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| 142 |
+
except Exception as e:
|
| 143 |
+
log("error", step="docs", err=repr(e)[:500])
|
| 144 |
+
|
| 145 |
+
n_up = sum(1 for r in results if r[1] == "uploaded")
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| 146 |
+
n_un = sum(1 for r in results if r[1] == "unchanged")
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| 147 |
+
n_fail = sum(1 for r in results if r[1] == "FAILED")
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| 148 |
+
log("run_done", uploaded=n_up, unchanged=n_un, failed=n_fail)
|
| 149 |
+
sys.exit(1 if n_fail else 0)
|
| 150 |
+
|
| 151 |
+
if __name__ == "__main__":
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| 152 |
+
main()
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