Spaces:
Running
on
A10G
Running
on
A10G
Update app.py
Browse files
app.py
CHANGED
@@ -23,14 +23,30 @@ def script_to_use(model_id, api):
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arch = arch[0]
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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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-
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print("Model downloaded successully!")
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conversion_script = script_to_use(model_id, api)
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@@ -49,7 +65,7 @@ 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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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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@@ -58,6 +74,7 @@ def process_model(model_id, q_method, hf_token):
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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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@@ -84,7 +101,7 @@ def process_model(model_id, q_method, hf_token):
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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
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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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@@ -138,6 +155,11 @@ iface = gr.Interface(
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label="HF Write Token",
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info="https://hf.co/settings/token",
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type="password",
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)
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],
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outputs=[
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@@ -145,7 +167,7 @@ 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
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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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arch = arch[0]
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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, private_repo):
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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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dl_pattern = ["*.md", "*.json", "*.model"]
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pattern = (
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"*.safetensors"
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if any(
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file.path.endswith(".safetensors")
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for file in api.list_repo_tree(
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repo_id=model_id,
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recursive=True,
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)
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)
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else "*.bin"
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)
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dl_pattern += pattern
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snapshot_download(repo_id=model_id, local_dir=model_name, local_dir_use_symlinks=False, token=hf_token, allow_patterns=dl_pattern)
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print("Model downloaded successully!")
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conversion_script = script_to_use(model_id, api)
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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, private=private_repo)
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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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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.data.tags += ["gguf-my-repo"]
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card.text = dedent(
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f"""
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# {new_repo_id}
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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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label="HF Write Token",
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info="https://hf.co/settings/token",
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type="password",
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),
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gr.Checkbox(
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value=False,
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label="Private Repo",
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info="Create a private repo under your username."
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)
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],
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outputs=[
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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 an HF repo as an input, quantises it and creates a Public 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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