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Running
on
A10G
Update app.py (#25)
Browse files- Update app.py (919ef918aa0878c9ca7f8812e1cdc5bb57ccd555)
app.py
CHANGED
@@ -30,12 +30,13 @@ def process_model(model_id, q_method, hf_token):
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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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@@ -52,26 +53,42 @@ def process_model(model_id, q_method, hf_token):
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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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-
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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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```bash
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brew install ggerganov/ggerganov/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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@@ -128,7 +145,7 @@ iface = gr.Interface(
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gr.Image(show_label=False),
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],
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title="Create your own GGUF Quants, blazingly fast ⚡!",
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description="The space takes a HF repo as an input, quantises it and creates
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article="<p>Find your write token at <a href='https://huggingface.co/settings/tokens' target='_blank'>token settings</a></p>",
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)
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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, token=hf_token)
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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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print(result)
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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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new_repo_id = new_repo_url.repo_id
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print("Repo created successfully!", new_repo_url)
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try:
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card = ModelCard.load(model_id,)
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except:
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card = ModelCard("")
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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 via the GGML.ai's [GGUF-it](https://huggingface.co/spaces/ggml-org/GGUF-it) space.
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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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Install Llama.cpp through brew.
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```bash
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brew install ggerganov/ggerganov/llama.cpp
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```
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Invoke the llama.cpp server or the CLI.
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CLI:
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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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Server:
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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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Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the llama.cpp repo as well.
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```
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git clone https://github.com/ggerganov/llama.cpp && cd llama.cpp && make && ./main -m {qtype.split("/")[-1]} -n 128
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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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gr.Image(show_label=False),
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],
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title="Create your own GGUF Quants, blazingly fast ⚡!",
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description="The space takes a HF repo as an input, quantises it and creates anoter repo containing the selected quant under your HF user namespace. You need to specify a write token obtained in https://hf.co/settings/tokens.",
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article="<p>Find your write token at <a href='https://huggingface.co/settings/tokens' target='_blank'>token settings</a></p>",
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)
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