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Update app.py
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app.py
CHANGED
@@ -2,17 +2,36 @@ import streamlit as st
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import torch
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from transformers import AutoModelForCausalLM
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import difflib
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@st.cache_data
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def get_model_structure(model_id):
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.bfloat16,
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device_map="cpu",
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)
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structure = {k: str(v.shape) for k, v in model.state_dict().items()}
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return structure
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def compare_structures(struct1, struct2):
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struct1_lines = [f"{k}: {v}" for k, v in struct1.items()]
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struct2_lines = [f"{k}: {v}" for k, v in struct2.items()]
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@@ -53,8 +72,8 @@ st.markdown(
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<style>
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.reportview-container .main .block-container {
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max-width: 100%;
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padding-left:
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padding-right:
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}
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.stMarkdown {
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white-space: pre-wrap;
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import torch
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from transformers import AutoModelForCausalLM
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import difflib
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import requests
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import os
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import json
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FIREBASE_URL = os.getenv("FIREBASE_URL")
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def fetch_from_firebase(model_id):
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response = requests.get(f"{FIREBASE_URL}/model_structures/{model_id}.json")
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if response.status_code == 200:
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return response.json()
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return None
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def save_to_firebase(model_id, structure):
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response = requests.put(f"{FIREBASE_URL}/model_structures/{model_id}.json", data=json.dumps(structure))
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return response.status_code == 200
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def get_model_structure(model_id):
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structure = fetch_from_firebase(model_id)
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if structure:
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return structure
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.bfloat16,
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device_map="cpu",
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)
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structure = {k: str(v.shape) for k, v in model.state_dict().items()}
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save_to_firebase(model_id, structure)
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return structure
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def compare_structures(struct1, struct2):
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struct1_lines = [f"{k}: {v}" for k, v in struct1.items()]
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struct2_lines = [f"{k}: {v}" for k, v in struct2.items()]
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<style>
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.reportview-container .main .block-container {
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max-width: 100%;
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padding-left: 10%;
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padding-right: 10%;
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}
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.stMarkdown {
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white-space: pre-wrap;
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