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Runtime error
Runtime error
Some cleaning in huggingface_hub integration (#13)
Browse files- Some cleaning in huggingface_hub integration (85fe931f3911f59e26cc6c4ca2f28c5d1affa26a)
Co-authored-by: Lucain Pouget <[email protected]>
app.py
CHANGED
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@@ -24,25 +24,23 @@ def script_to_use(model_id, api):
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return "convert.py" if arch in LLAMA_LIKE_ARCHS else "convert-hf-to-gguf.py"
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def process_model(model_id, q_method, hf_token):
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fp16 = f"{
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try:
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api = HfApi(token=hf_token)
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-
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snapshot_download(repo_id=model_id, local_dir = f"{MODEL_NAME}", local_dir_use_symlinks=False)
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print("Model downloaded successully!")
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conversion_script = script_to_use(model_id, api)
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fp16_conversion = f"python llama.cpp/{conversion_script} {
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result = subprocess.run(fp16_conversion, shell=True, capture_output=True)
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if result.returncode != 0:
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raise Exception(f"Error converting to fp16: {result.stderr}")
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print("Model converted to fp16 successully!")
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qtype = f"{
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quantise_ggml = f"./llama.cpp/quantize {fp16} {qtype} {q_method}"
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result = subprocess.run(quantise_ggml, shell=True, capture_output=True)
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if result.returncode != 0:
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@@ -50,20 +48,15 @@ def process_model(model_id, q_method, hf_token):
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print("Quantised successfully!")
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# Create empty repo
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-
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repo_type="model",
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exist_ok=True,
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token=hf_token
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)
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print("Repo created successfully!")
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card = ModelCard.load(model_id)
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card.data.tags = ["llama-cpp"] if card.data.tags is None else card.data.tags + ["llama-cpp"]
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card.text = dedent(
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f"""
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# {
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This model was converted to GGUF format from [`{model_id}`](https://huggingface.co/{model_id}) using llama.cpp.
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Refer to the [original model card](https://huggingface.co/{model_id}) for more details on the model.
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## Use with llama.cpp
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@@ -73,39 +66,37 @@ def process_model(model_id, q_method, hf_token):
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```
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```bash
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llama-cli --hf-repo {
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```
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```bash
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llama-server --hf-repo {
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```
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"""
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)
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card.save(os.path.join(
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api.upload_file(
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path_or_fileobj=qtype,
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path_in_repo=qtype.split("/")[-1],
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repo_id=
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repo_type="model",
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)
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api.upload_file(
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path_or_fileobj=f"{
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path_in_repo="README.md",
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repo_id=
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repo_type="model",
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)
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print("Uploaded successfully!")
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return (
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f'Find your repo <a href=\'{
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"llama.png",
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)
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except Exception as e:
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return (f"Error: {e}", "error.png")
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finally:
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shutil.rmtree(
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print("Folder cleaned up successfully!")
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return "convert.py" if arch in LLAMA_LIKE_ARCHS else "convert-hf-to-gguf.py"
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def process_model(model_id, q_method, hf_token):
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model_name = model_id.split('/')[-1]
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fp16 = f"{model_name}/{model_name.lower()}.fp16.bin"
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try:
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api = HfApi(token=hf_token)
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snapshot_download(repo_id=model_id, local_dir=model_name, local_dir_use_symlinks=False)
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print("Model downloaded successully!")
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conversion_script = script_to_use(model_id, api)
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fp16_conversion = f"python llama.cpp/{conversion_script} {model_name} --outtype f16 --outfile {fp16}"
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result = subprocess.run(fp16_conversion, shell=True, capture_output=True)
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if result.returncode != 0:
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raise Exception(f"Error converting to fp16: {result.stderr}")
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print("Model converted to fp16 successully!")
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qtype = f"{model_name}/{model_name.lower()}.{q_method.upper()}.gguf"
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quantise_ggml = f"./llama.cpp/quantize {fp16} {qtype} {q_method}"
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result = subprocess.run(quantise_ggml, shell=True, capture_output=True)
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if result.returncode != 0:
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print("Quantised successfully!")
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# Create empty repo
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new_repo_url = api.create_repo(repo_id=f"{model_name}-{q_method}-GGUF", exist_ok=True)
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new_repo_id = new_repo_url.repo_id
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print("Repo created successfully!", new_repo_url)
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card = ModelCard.load(model_id)
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card.data.tags = ["llama-cpp"] if card.data.tags is None else card.data.tags + ["llama-cpp"]
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card.text = dedent(
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f"""
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# {new_repo_id}
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This model was converted to GGUF format from [`{model_id}`](https://huggingface.co/{model_id}) using llama.cpp.
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Refer to the [original model card](https://huggingface.co/{model_id}) for more details on the model.
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## Use with llama.cpp
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```
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```bash
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llama-cli --hf-repo {new_repo_id} --model {qtype.split("/")[-1]} -p "The meaning to life and the universe is "
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```
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```bash
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llama-server --hf-repo {new_repo_id} --model {qtype.split("/")[-1]} -c 2048
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```
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"""
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)
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card.save(os.path.join(model_name, "README-new.md"))
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api.upload_file(
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path_or_fileobj=qtype,
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path_in_repo=qtype.split("/")[-1],
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repo_id=new_repo_id,
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)
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api.upload_file(
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path_or_fileobj=f"{model_name}/README-new.md",
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path_in_repo="README.md",
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repo_id=new_repo_id,
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)
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print("Uploaded successfully!")
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return (
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f'Find your repo <a href=\'{new_repo_url}\' target="_blank" style="text-decoration:underline">here</a>',
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"llama.png",
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)
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except Exception as e:
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return (f"Error: {e}", "error.png")
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finally:
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shutil.rmtree(model_name, ignore_errors=True)
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print("Folder cleaned up successfully!")
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