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Update app.py (#7)
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app.py
CHANGED
@@ -1,3 +1,4 @@
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import shutil
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import subprocess
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@@ -6,6 +7,9 @@ import gradio as gr
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from huggingface_hub import create_repo, HfApi
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from huggingface_hub import snapshot_download
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from huggingface_hub import whoami
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api = HfApi()
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@@ -29,26 +33,50 @@ 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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repo_url = create_repo(
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repo_id =
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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("Empty repo created successfully!")
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api.upload_file(
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path_or_fileobj=qtype,
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-
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repo_type="model",
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)
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print("Uploaded successfully!")
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shutil.rmtree(MODEL_NAME)
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import os
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import shutil
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import subprocess
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from huggingface_hub import create_repo, HfApi
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from huggingface_hub import snapshot_download
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from huggingface_hub import whoami
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from huggingface_hub import ModelCard
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from textwrap import dedent
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api = HfApi()
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print("Quantised successfully!")
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# Create empty repo
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repo_id = f"{username}/{MODEL_NAME}-{q_method}-GGUF"
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repo_url = create_repo(
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repo_id = repo_id,
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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("Empty 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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# {upload_repo}
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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 {repo_id} --model {qtype.split("/")[-1]} -p "The meaning to life and the universe is "
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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=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"{MODEL_NAME}/README-new.md",
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path_in_repo=README.md,
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repo_id=repo_id,
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repo_type="model",
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)
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print("Uploaded successfully!")
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shutil.rmtree(MODEL_NAME)
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