Upload convert_survival_32b_gguf.py with huggingface_hub

convert_survival_32b_gguf.py

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+
+# /// script
+# dependencies = ["peft", "transformers", "torch", "huggingface_hub", "sentencepiece", "cmake"]
+# ///
+
+import os
+import subprocess
+from peft import PeftModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from huggingface_hub import HfApi, create_repo
+import torch
+
+# Configuration
+BASE_MODEL_ID = "Qwen/Qwen2.5-32B-Instruct"
+ADAPTER_ID = "sunkencity/survival-expert-qwen-32b"
+OUTPUT_REPO = "sunkencity/survival-expert-qwen-32b-gguf"
+MERGED_DIR = "merged_model"
+GGUF_FILE = "survival-expert-qwen-32b.Q4_K_M.gguf"
+
+print(f"Loading base model: {BASE_MODEL_ID}")
+# Load in bfloat16 to save memory and match training
+base_model = AutoModelForCausalLM.from_pretrained(
+    BASE_MODEL_ID,
+    device_map="auto",
+    torch_dtype=torch.bfloat16,
+    trust_remote_code=True
+)
+
+print(f"Loading adapter: {ADAPTER_ID}")
+model = PeftModel.from_pretrained(base_model, ADAPTER_ID)
+
+print("Merging model...")
+model = model.merge_and_unload()
+
+print(f"Saving merged model to {MERGED_DIR}...")
+model.save_pretrained(MERGED_DIR)
+tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL_ID)
+tokenizer.save_pretrained(MERGED_DIR)
+
+print("Cloning llama.cpp...")
+if os.path.exists("llama.cpp"):
+    subprocess.run(["rm", "-rf", "llama.cpp"])
+subprocess.run(["git", "clone", "https://github.com/ggerganov/llama.cpp"], check=True)
+
+print("Installing llama.cpp requirements...")
+subprocess.run(["pip", "install", "-r", "llama.cpp/requirements.txt"], check=True)
+
+print("Building llama-quantize with CMake...")
+os.makedirs("llama.cpp/build", exist_ok=True)
+subprocess.run(["cmake", "-B", "llama.cpp/build", "-S", "llama.cpp"], check=True)
+subprocess.run(["cmake", "--build", "llama.cpp/build", "--config", "Release", "-j"], check=True)
+
+print("Converting to GGUF (FP16)...")
+# Convert to GGUF (BF16/FP16 preserved from model)
+subprocess.run([
+    "python", "llama.cpp/convert_hf_to_gguf.py",
+    MERGED_DIR,
+    "--outfile", "merged_model.gguf",
+    "--outtype", "bf16" 
+], check=True)
+
+print("Quantizing to Q4_K_M...")
+quantize_bin = "llama.cpp/build/bin/llama-quantize"
+subprocess.run([
+    quantize_bin,
+    "merged_model.gguf",
+    GGUF_FILE,
+    "Q4_K_M"
+], check=True)
+
+print(f"Creating repo {OUTPUT_REPO}...")
+api = HfApi()
+create_repo(OUTPUT_REPO, repo_type="model", exist_ok=True)
+
+print(f"Uploading {GGUF_FILE}...")
+api.upload_file(
+    path_or_fileobj=GGUF_FILE,
+    path_in_repo=GGUF_FILE,
+    repo_id=OUTPUT_REPO,
+    repo_type="model"
+)
+
+print("Done! GGUF available at:", f"https://huggingface.co/{OUTPUT_REPO}")