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import os |
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import requests |
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import zipfile |
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import subprocess |
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import shutil |
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from huggingface_hub import snapshot_download |
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def clone_or_update_llama_cpp(): |
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print("Preparing...") |
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base_dir = os.path.dirname(os.path.abspath(__file__)) |
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os.chdir(base_dir) |
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if not os.path.exists("llama.cpp"): |
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subprocess.run(["git", "clone", "--depth", "1", "https://github.com/ggerganov/llama.cpp"]) |
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else: |
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os.chdir("llama.cpp") |
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subprocess.run(["git", "pull"]) |
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os.chdir(base_dir) |
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print("The 'llama.cpp' repository is ready.") |
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def download_llama_release(): |
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base_dir = os.path.dirname(os.path.abspath(__file__)) |
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dl_dir = os.path.join(base_dir, "bin", "dl") |
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if not os.path.exists(dl_dir): |
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os.makedirs(dl_dir) |
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os.chdir(dl_dir) |
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latest_release_url = "https://github.com/ggerganov/llama.cpp/releases/latest" |
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response = requests.get(latest_release_url) |
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if response.status_code == 200: |
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latest_release_tag = response.url.split("/")[-1] |
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download_url = f"https://github.com/ggerganov/llama.cpp/releases/download/{latest_release_tag}/llama-{latest_release_tag}-bin-win-cuda-cu12.2.0-x64.zip" |
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response = requests.get(download_url) |
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if response.status_code == 200: |
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with open(f"llama-{latest_release_tag}-bin-win-cuda-cu12.2.0-x64.zip", "wb") as f: |
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f.write(response.content) |
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with zipfile.ZipFile(f"llama-{latest_release_tag}-bin-win-cuda-cu12.2.0-x64.zip", "r") as zip_ref: |
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zip_ref.extractall(os.path.join(base_dir, "bin")) |
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print("Downloading latest 'llama.cpp' prebuilt Windows binaries...") |
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print("Download and extraction completed successfully.") |
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return latest_release_tag |
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else: |
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print("Failed to download the release file.") |
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else: |
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print("Failed to fetch the latest release information.") |
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def download_cudart_if_necessary(latest_release_tag): |
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base_dir = os.path.dirname(os.path.abspath(__file__)) |
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cudart_dl_dir = os.path.join(base_dir, "bin", "dl") |
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if not os.path.exists(cudart_dl_dir): |
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os.makedirs(cudart_dl_dir) |
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cudart_zip_file = os.path.join(cudart_dl_dir, "cudart-llama-bin-win-cu12.2.0-x64.zip") |
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cudart_extracted_files = ["cublas64_12.dll", "cublasLt64_12.dll", "cudart64_12.dll"] |
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if all(os.path.exists(os.path.join(base_dir, "bin", file)) for file in cudart_extracted_files): |
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print("Cuda resources already exist. Skipping download.") |
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else: |
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cudart_download_url = f"https://github.com/ggerganov/llama.cpp/releases/download/{latest_release_tag}/cudart-llama-bin-win-cu12.2.0-x64.zip" |
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response = requests.get(cudart_download_url) |
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if response.status_code == 200: |
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with open(cudart_zip_file, "wb") as f: |
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f.write(response.content) |
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with zipfile.ZipFile(cudart_zip_file, "r") as zip_ref: |
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zip_ref.extractall(os.path.join(base_dir, "bin")) |
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print("Preparing 'cuda' resources...") |
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print("Download and extraction of cudart completed successfully.") |
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else: |
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print("Failed to download the cudart release file.") |
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def download_model_repo(): |
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base_dir = os.path.dirname(os.path.abspath(__file__)) |
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models_dir = os.path.join(base_dir, "models") |
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if not os.path.exists(models_dir): |
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os.makedirs(models_dir) |
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model_id = input("Enter the model ID to download (e.g., huggingface/transformers): ") |
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model_name = model_id.split("/")[-1] |
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model_dir = os.path.join(models_dir, model_name) |
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gguf_dir = os.path.join(base_dir, "models", f"{model_name}-GGUF") |
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gguf_model_path = os.path.join(gguf_dir, f"{model_name}-F16.gguf") |
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imatrix_file_name = input("Enter the name of the imatrix.txt file (default: imatrix.txt): ").strip() or "imatrix.txt" |
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delete_model_dir = input("Remove HF model folder after converting original model to GGUF? (yes/no) (default: no): ").strip().lower() |
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if os.path.exists(gguf_model_path): |
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create_imatrix(base_dir, gguf_dir, gguf_model_path, model_name, imatrix_file_name) |
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else: |
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if os.path.exists(model_dir): |
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print("Model repository already exists. Using existing repository.") |
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convert_model_to_gguf_f16(base_dir, model_dir, model_name, delete_model_dir, imatrix_file_name) |
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else: |
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revision = input("Enter the revision (branch, tag, or commit) to download (default: main): ") or "main" |
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print("Downloading model repository...") |
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snapshot_download(repo_id=model_id, local_dir=model_dir, revision=revision) |
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print("Model repository downloaded successfully.") |
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convert_model_to_gguf_f16(base_dir, model_dir, model_name, delete_model_dir, imatrix_file_name) |
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def convert_model_to_gguf_f16(base_dir, model_dir, model_name, delete_model_dir, imatrix_file_name): |
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convert_script = os.path.join(base_dir, "llama.cpp", "convert.py") |
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gguf_dir = os.path.join(base_dir, "models", f"{model_name}-GGUF") |
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gguf_model_path = os.path.join(gguf_dir, f"{model_name}-F16.gguf") |
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if not os.path.exists(gguf_dir): |
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os.makedirs(gguf_dir) |
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if not os.path.exists(gguf_model_path): |
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subprocess.run(["python", convert_script, model_dir, "--outfile", gguf_model_path, "--outtype", "f16", "--vocab-type", "bpe"]) |
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if delete_model_dir == 'yes' or delete_model_dir == 'y': |
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shutil.rmtree(model_dir) |
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print(f"Original model directory '{model_dir}' deleted.") |
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else: |
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print(f"Original model directory '{model_dir}' was not deleted. You can remove it manually.") |
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create_imatrix(base_dir, gguf_dir, gguf_model_path, model_name, imatrix_file_name) |
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def create_imatrix(base_dir, gguf_dir, gguf_model_path, model_name, imatrix_file_name): |
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imatrix_exe = os.path.join(base_dir, "bin", "imatrix.exe") |
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imatrix_output_src = os.path.join(gguf_dir, "imatrix.dat") |
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imatrix_output_dst = os.path.join(gguf_dir, "imatrix.dat") |
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if not os.path.exists(imatrix_output_dst): |
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try: |
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subprocess.run([imatrix_exe, "-m", gguf_model_path, "-f", os.path.join(base_dir, "imatrix", imatrix_file_name), "-ngl", "8"], cwd=gguf_dir) |
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shutil.move(imatrix_output_src, imatrix_output_dst) |
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print("imatrix.dat moved successfully.") |
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except Exception as e: |
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print("Error occurred while moving imatrix.dat:", e) |
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else: |
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print("imatrix.dat already exists in the GGUF folder.") |
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quantize_models(base_dir, model_name) |
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def quantize_models(base_dir, model_name): |
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gguf_dir = os.path.join(base_dir, "models", f"{model_name}-GGUF") |
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f16_gguf_path = os.path.join(gguf_dir, f"{model_name}-F16.gguf") |
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quantization_options = [ |
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"IQ3_M", "IQ3_XXS", |
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"Q4_K_M", "Q4_K_S", "IQ4_NL", "IQ4_XS", |
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"Q5_K_M", "Q5_K_S", |
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"Q6_K", |
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"Q8_0" |
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] |
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for quant_option in quantization_options: |
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quantized_gguf_name = f"{model_name}-{quant_option}-imat.gguf" |
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quantized_gguf_path = os.path.join(gguf_dir, quantized_gguf_name) |
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quantize_command = os.path.join(base_dir, "bin", "quantize.exe") |
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imatrix_path = os.path.join(gguf_dir, "imatrix.dat") |
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subprocess.run([quantize_command, "--imatrix", imatrix_path, |
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f16_gguf_path, quantized_gguf_path, quant_option], cwd=gguf_dir) |
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print(f"Model quantized with {quant_option} option.") |
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def main(): |
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clone_or_update_llama_cpp() |
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latest_release_tag = download_llama_release() |
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download_cudart_if_necessary(latest_release_tag) |
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download_model_repo() |
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print("Finished preparing resources.") |
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if __name__ == "__main__": |
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main() |