99 lines
3.5 KiB
Python
99 lines
3.5 KiB
Python
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#!/usr/bin/env python3
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"""
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Convert zindango-slm to GGUF and push to Hugging Face.
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Requires: llama.cpp cloned, gguf, sentencepiece
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pip install gguf sentencepiece
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git clone https://github.com/ggml-org/llama.cpp
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Usage:
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python scripts/convert_and_push_gguf.py [--model-dir PATH] [--quantize Q4_K_M]
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"""
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import argparse
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import subprocess
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import sys
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from pathlib import Path
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from huggingface_hub import HfApi, create_repo, upload_folder, upload_file
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--model-dir", default="outputs/zindango-slm-20260215_124754")
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parser.add_argument("--llama-cpp", default="/home/piren/projects/llama.cpp")
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parser.add_argument("--quantize", choices=["q4_k_m", "q5_k_m", "q8_0", "none"], default="none")
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parser.add_argument("--repo-id", default=None)
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parser.add_argument("--skip-create", action="store_true")
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parser.add_argument("--push-only", action="store_true", help="Skip conversion, only push existing GGUF")
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args = parser.parse_args()
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project_root = Path(__file__).resolve().parent.parent
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model_dir = project_root / args.model_dir
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out_dir = project_root / "outputs"
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f16_gguf = out_dir / "zindango-slm-f16.gguf"
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if not args.push_only:
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llama_cpp = Path(args.llama_cpp)
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if not (llama_cpp / "convert_hf_to_gguf.py").exists():
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raise SystemExit(f"llama.cpp not found at {llama_cpp}. Clone it first.")
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if not model_dir.exists():
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raise SystemExit(f"Model not found: {model_dir}")
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# Convert to F16 GGUF
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cmd = [
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sys.executable,
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str(llama_cpp / "convert_hf_to_gguf.py"),
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str(model_dir),
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"--outtype", "f16",
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"--outfile", str(f16_gguf),
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]
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print("Converting to GGUF f16...")
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subprocess.run(cmd, check=True)
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# Optionally quantize
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if args.quantize != "none":
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quant_bin = llama_cpp / "build" / "bin" / "llama-quantize"
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if not quant_bin.exists():
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quant_bin = llama_cpp / "bin" / "llama-quantize"
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if quant_bin.exists():
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q_gguf = out_dir / f"zindango-slm-{args.quantize}.gguf"
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cmd = [str(quant_bin), str(f16_gguf), str(q_gguf), args.quantize.upper()]
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print(f"Quantizing to {args.quantize}...")
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subprocess.run(cmd, check=True)
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else:
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print("llama-quantize not found; skipping quantization")
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# Push to Hub
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api = HfApi()
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user = api.whoami()
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username = user["name"]
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repo_id = args.repo_id or f"{username}/zindango-slm"
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if not args.skip_create:
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try:
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create_repo(repo_id, repo_type="model", exist_ok=True)
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except Exception as e:
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if "403" in str(e).lower() or "forbidden" in str(e).lower():
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print("Create repo failed. Run with --skip-create after creating manually.")
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raise
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# Upload GGUF file(s): f16 + any quantized (q4_k_m, q8_0, etc.)
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quant_ggufs = list(out_dir.glob("zindango-slm-q*.gguf")) + list(out_dir.glob("zindango-slm-Q*.gguf"))
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for gguf_path in [f16_gguf] + quant_ggufs:
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if gguf_path.exists():
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print(f"Uploading {gguf_path.name}...")
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upload_file(
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path_or_fileobj=str(gguf_path),
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path_in_repo=gguf_path.name,
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repo_id=repo_id,
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repo_type="model",
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commit_message=f"Add {gguf_path.name}",
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)
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print(f"Done. Model: https://huggingface.co/{repo_id}")
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if __name__ == "__main__":
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main()
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