Initial commit

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

.gitignore

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+.venv
+.streamlit
+transformers.js

README.md

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+---
+title: Convert to ONNX
+emoji: ☯
+colorFrom: indigo
+colorTo: yellow
+sdk: streamlit
+sdk_version: 1.31.1
+app_file: app.py
+pinned: true
+license: apache-2.0
+short_description: Convert a HuggingFace model to ONNX format
+---

app.py

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+import streamlit as st
+from huggingface_hub import HfApi
+import os
+import subprocess
+
+HF_TOKEN = st.secrets.get("HF_TOKEN") or os.environ.get("HF_TOKEN")
+HF_USERNAME = (
+    st.secrets.get("HF_USERNAME")
+    or os.environ.get("HF_USERNAME")
+    or os.environ.get("SPACE_AUTHOR_NAME")
+)
+TRANSFORMERS_REPOSITORY_URL = "https://github.com/xenova/transformers.js"
+TRANSFORMERS_REPOSITORY_REVISION = "2.16.0"
+TRANSFORMERS_REPOSITORY_PATH = "./transformers.js"
+HF_BASE_URL = "https://huggingface.co"
+
+if not os.path.exists(TRANSFORMERS_REPOSITORY_PATH):
+    os.system(f"git clone {TRANSFORMERS_REPOSITORY_URL} {TRANSFORMERS_REPOSITORY_PATH}")
+
+os.system(
+    f"cd {TRANSFORMERS_REPOSITORY_PATH} && git checkout {TRANSFORMERS_REPOSITORY_REVISION}"
+)
+
+st.write("## Convert a HuggingFace model to ONNX")
+
+input_model_id = st.text_input(
+    "Enter the HuggingFace model ID to convert. Example: `EleutherAI/pythia-14m`"
+)
+
+if input_model_id:
+    model_name = (
+        input_model_id.replace(f"{HF_BASE_URL}/", "")
+        .replace("/", "-")
+        .replace(f"{HF_USERNAME}-", "")
+        .strip()
+    )
+    output_model_id = f"{HF_USERNAME}/{model_name}-ONNX"
+    output_model_url = f"{HF_BASE_URL}/{output_model_id}"
+    api = HfApi(token=HF_TOKEN)
+    repo_exists = api.repo_exists(output_model_id)
+
+    if repo_exists:
+        st.write("This model has already been converted! 🎉")
+        st.link_button(f"Go to {output_model_id}", output_model_url, type="primary")
+    else:
+        st.write(f"This model will be converted and uploaded to the following URL:")
+        st.code(output_model_url, language="plaintext")
+        start_conversion = st.button(label="Proceed", type="primary")
+
+        if start_conversion:
+            with st.spinner("Converting model..."):
+                output = subprocess.run(
+                    [
+                        "python",
+                        "-m",
+                        "scripts.convert",
+                        "--quantize",
+                        "--model_id",
+                        input_model_id,
+                    ],
+                    cwd=TRANSFORMERS_REPOSITORY_PATH,
+                    capture_output=True,
+                    text=True,
+                )
+
+            model_folder_path = (
+                f"{TRANSFORMERS_REPOSITORY_PATH}/models/{input_model_id}"
+            )
+
+            os.rename(
+                f"{model_folder_path}/onnx/model.onnx",
+                f"{model_folder_path}/onnx/decoder_model_merged.onnx",
+            )
+            os.rename(
+                f"{model_folder_path}/onnx/model_quantized.onnx",
+                f"{model_folder_path}/onnx/decoder_model_merged_quantized.onnx",
+            )
+
+            st.success("Conversion successful!")
+
+            st.code(output.stderr)
+
+            with st.spinner("Uploading model..."):
+                repository = api.create_repo(
+                    f"{output_model_id}", exist_ok=True, private=False
+                )
+
+                upload_error_message = None
+
+                try:
+                    api.upload_folder(
+                        folder_path=model_folder_path, repo_id=repository.repo_id
+                    )
+                except Exception as e:
+                    upload_error_message = str(e)
+
+            os.system(f"rm -rf {model_folder_path}")
+
+            if upload_error_message:
+                st.error(f"Upload failed: {upload_error_message}")
+            else:
+                st.success(f"Upload successful!")
+                st.write("You can now go and view the model on HuggingFace!")
+                st.link_button(
+                    f"Go to {output_model_id}", output_model_url, type="primary"
+                )

license.txt

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requirements.txt

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+transformers[torch]==4.35.2
+onnxruntime<1.16.0
+optimum==1.14.1
+tqdm
+onnx==1.13.1
+huggingface_hub
+streamlit

run.sh

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+#!/bin/sh
+pip install -r requirements.txt
+streamlit run app.py