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app/__pycache__/draw_diagram.cpython-312.pyc
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app/__pycache__/draw_diagram_test.cpython-312.pyc
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app/__pycache__/pages.cpython-312.pyc
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app/draw_diagram.py
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@@ -6,67 +6,67 @@ from streamlit_echarts import st_echarts
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from streamlit_javascript import st_javascript
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# from PIL import Image
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links_dic = {"random": "https://seaeval.github.io/",
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links_dic = {k.lower().replace('_', '-') : v for k, v in links_dic.items()}
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# huggingface_image = Image.open('style/huggingface.jpg')
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def nav_to(value):
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def highlight_table_line(model_name):
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def draw_cross_lingual(category_one, category_two, sort, sorted):
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@@ -85,6 +85,16 @@ def draw_cross_lingual(category_one, category_two, sort, sorted):
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min_value = round(chart_data.iloc[:, 1::].min().min() - 0.1, 1)
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max_value = round(chart_data.iloc[:, 1::].max().max() + 0.1, 1)
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if category_two in ['cross_mmlu', 'cross_logiqa']:
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# print(category_two)
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@@ -109,14 +119,15 @@ def draw_cross_lingual(category_one, category_two, sort, sorted):
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"xAxis": [
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{
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"type": "category",
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"boundaryGap":
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"triggerEvent": True,
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"data":
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}
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],
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"yAxis": [{"type": "value",
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"min": min_value,
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"max": max_value,
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# "splitNumber": 10
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}],
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"series": [
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],
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}
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events = {
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}
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value = st_echarts(options=options,
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if value != None:
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# if value != None:
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# highlight_table_line(value)
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"xAxis": [
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{
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"type": "category",
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"boundaryGap":
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"data":
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}
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],
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"yAxis": [{"type": "value",
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"min": min_value,
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"max": max_value,
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# "splitNumber": 10
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}],
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"series": [
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@@ -255,15 +267,15 @@ def draw_cross_lingual(category_one, category_two, sort, sorted):
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],
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}
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events = {
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}
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value = st_echarts(options=options,
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if value != None:
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# if value != None:
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# highlight_table_line(value)
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@@ -321,6 +333,16 @@ def draw_only_acc(folder_name, category_one, category_two, sorted):
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subtitle = category_two_dict[category_two]
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data_path = f'{folder}/{category_one}/{subtitle}.csv'
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chart_data = pd.read_csv(data_path).round(3)
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if sorted == 'Ascending':
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ascend = True
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"xAxis": [
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{
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"type": "category",
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"boundaryGap":
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"triggerEvent": True,
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"data":
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}
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],
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"yAxis": [{"type": "value",
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"min": min_value,
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"max": max_value,
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# "splitNumber": 10
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}],
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"series": [
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@@ -365,15 +388,15 @@ def draw_only_acc(folder_name, category_one, category_two, sorted):
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],
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}
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events = {
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-
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}
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value = st_echarts(options=options,
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if value != None:
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# if value != None:
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# highlight_table_line(value)
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@@ -412,6 +435,16 @@ def draw_flores_translation(category_one, category_two, sorted):
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min_value = round(chart_data.iloc[:, 1::].min().min() - 0.1, 1)
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max_value = round(chart_data.iloc[:, 1::].max().max() + 0.1, 1)
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options = {
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"title": {"text": f"{category_two}"},
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"tooltip": {
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"xAxis": [
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{
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"type": "category",
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"boundaryGap":
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"triggerEvent": True,
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"data":
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}
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],
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"yAxis": [{"type": "value",
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"min": min_value,
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"max": max_value,
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# "splitNumber": 10
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}],
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"series": [
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@@ -445,15 +479,15 @@ def draw_flores_translation(category_one, category_two, sorted):
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],
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}
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events = {
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}
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value = st_echarts(options=options,
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if value != None:
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### create table
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data_path = f'{folder}/{category_one}/{subtitle}.csv'
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chart_data = pd.read_csv(data_path).round(3)
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if sorted == 'Ascending':
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ascend = True
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else:
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"xAxis": [
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{
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"type": "category",
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"boundaryGap":
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"triggerEvent": True,
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"data":
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}
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],
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"yAxis": [{"type": "value",
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"min": min_value,
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"max": max_value,
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# "splitNumber": 10
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}],
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"series": [
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"xAxis": [
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{
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"type": "category",
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"boundaryGap":
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"triggerEvent": True,
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"data":
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}
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],
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"yAxis": [{"type": "value",
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"min": min_value,
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"max": max_value,
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# "splitNumber": 10
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}],
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"series": [
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{
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],
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}
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events = {
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}
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value = st_echarts(options=options,
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if value != None:
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### create table
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from streamlit_javascript import st_javascript
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# from PIL import Image
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# links_dic = {"random": "https://seaeval.github.io/",
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# "meta_llama_3_8b": "https://huggingface.co/meta-llama/Meta-Llama-3-8B",
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# "mistral_7b_instruct_v0_2": "https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2",
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# "sailor_0_5b": "https://huggingface.co/sail/Sailor-0.5B",
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# "sailor_1_8b": "https://huggingface.co/sail/Sailor-1.8B",
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# "sailor_4b": "https://huggingface.co/sail/Sailor-4B",
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# "sailor_7b": "https://huggingface.co/sail/Sailor-7B",
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# "sailor_0_5b_chat": "https://huggingface.co/sail/Sailor-0.5B-Chat",
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# "sailor_1_8b_chat": "https://huggingface.co/sail/Sailor-1.8B-Chat",
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# "sailor_4b_chat": "https://huggingface.co/sail/Sailor-4B-Chat",
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# "sailor_7b_chat": "https://huggingface.co/sail/Sailor-7B-Chat",
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# "sea_mistral_highest_acc_inst_7b": "https://seaeval.github.io/",
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# "meta_llama_3_8b_instruct": "https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct",
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# "flan_t5_base": "https://huggingface.co/google/flan-t5-base",
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# "flan_t5_large": "https://huggingface.co/google/flan-t5-large",
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# "flan_t5_xl": "https://huggingface.co/google/flan-t5-xl",
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# "flan_t5_xxl": "https://huggingface.co/google/flan-t5-xxl",
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# "flan_ul2": "https://huggingface.co/google/flan-t5-ul2",
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# "flan_t5_small": "https://huggingface.co/google/flan-t5-small",
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# "mt0_xxl": "https://huggingface.co/bigscience/mt0-xxl",
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# "seallm_7b_v2": "https://huggingface.co/SeaLLMs/SeaLLM-7B-v2",
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# "gpt_35_turbo_1106": "https://openai.com/blog/chatgpt",
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# "meta_llama_3_70b": "https://huggingface.co/meta-llama/Meta-Llama-3-70B",
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# "meta_llama_3_70b_instruct": "https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct",
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# "sea_lion_3b": "https://huggingface.co/aisingapore/sea-lion-3b",
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# "sea_lion_7b": "https://huggingface.co/aisingapore/sea-lion-7b",
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# "qwen1_5_110b": "https://huggingface.co/Qwen/Qwen1.5-110B",
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# "qwen1_5_110b_chat": "https://huggingface.co/Qwen/Qwen1.5-110B-Chat",
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# "llama_2_7b_chat": "https://huggingface.co/meta-llama/Llama-2-7b-chat-hf",
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# "gpt4_1106_preview": "https://openai.com/blog/chatgpt",
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# "gemma_2b": "https://huggingface.co/google/gemma-2b",
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# "gemma_7b": "https://huggingface.co/google/gemma-7b",
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# "gemma_2b_it": "https://huggingface.co/google/gemma-2b-it",
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# "gemma_7b_it": "https://huggingface.co/google/gemma-7b-it",
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# "qwen_1_5_7b": "https://huggingface.co/Qwen/Qwen1.5-7B",
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# "qwen_1_5_7b_chat": "https://huggingface.co/Qwen/Qwen1.5-7B-Chat",
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| 45 |
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# "sea_lion_7b_instruct": "https://huggingface.co/aisingapore/sea-lion-7b-instruct",
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# "sea_lion_7b_instruct_research": "https://huggingface.co/aisingapore/sea-lion-7b-instruct-research",
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| 47 |
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# "LLaMA_3_Merlion_8B": "https://seaeval.github.io/",
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| 48 |
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# "LLaMA_3_Merlion_8B_v1_1": "https://seaeval.github.io/"}
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# links_dic = {k.lower().replace('_', '-') : v for k, v in links_dic.items()}
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# # huggingface_image = Image.open('style/huggingface.jpg')
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# def nav_to(value):
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# try:
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# url = links_dic[str(value).lower()]
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# js = f'window.open("{url}", "_blank").then(r => window.parent.location.href);'
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# st_javascript(js)
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# except:
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# pass
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# # nav_script = """
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# # <meta http-equiv="refresh" content="0; url='%s'">
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# # """ % (url)
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# # st.write(nav_script, unsafe_allow_html=True)
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# def highlight_table_line(model_name):
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# st.write(model_name)
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def draw_cross_lingual(category_one, category_two, sort, sorted):
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min_value = round(chart_data.iloc[:, 1::].min().min() - 0.1, 1)
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max_value = round(chart_data.iloc[:, 1::].max().max() + 0.1, 1)
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+
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st.markdown("""
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<style>
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.stMultiSelect [data-baseweb=select] span{
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max-width: 800px;
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font-size: 0.9rem;
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}
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</style>
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""", unsafe_allow_html=True)
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models = st.multiselect("Please choose the models", chart_data['Model'].tolist(), default = chart_data['Model'].tolist())
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if category_two in ['cross_mmlu', 'cross_logiqa']:
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# print(category_two)
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"xAxis": [
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{
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"type": "category",
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"boundaryGap": True,
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"triggerEvent": True,
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"data": models,
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}
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],
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"yAxis": [{"type": "value",
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"min": min_value,
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"max": max_value,
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"boundaryGap": True
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# "splitNumber": 10
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}],
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"series": [
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],
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}
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# events = {
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# "click": "function(params) { return params.value }",
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# # "dblclick": "function(params) { return params.value }"
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# }
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value = st_echarts(options=options, height="500px") #events=events,
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# if value != None:
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# # print(value)
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# nav_to(value)
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# if value != None:
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# highlight_table_line(value)
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"xAxis": [
|
| 219 |
{
|
| 220 |
"type": "category",
|
| 221 |
+
"boundaryGap": True,
|
| 222 |
+
"data": models,
|
| 223 |
}
|
| 224 |
],
|
| 225 |
"yAxis": [{"type": "value",
|
| 226 |
"min": min_value,
|
| 227 |
"max": max_value,
|
| 228 |
+
"boundaryGap": True
|
| 229 |
# "splitNumber": 10
|
| 230 |
}],
|
| 231 |
"series": [
|
|
|
|
| 267 |
],
|
| 268 |
}
|
| 269 |
|
| 270 |
+
# events = {
|
| 271 |
+
# "click": "function(params) { return params.value }"
|
| 272 |
+
# }
|
| 273 |
|
| 274 |
+
value = st_echarts(options=options, height="500px")
|
| 275 |
|
| 276 |
+
# if value != None:
|
| 277 |
+
# # print(value)
|
| 278 |
+
# nav_to(value)
|
| 279 |
|
| 280 |
# if value != None:
|
| 281 |
# highlight_table_line(value)
|
|
|
|
| 333 |
subtitle = category_two_dict[category_two]
|
| 334 |
data_path = f'{folder}/{category_one}/{subtitle}.csv'
|
| 335 |
chart_data = pd.read_csv(data_path).round(3)
|
| 336 |
+
|
| 337 |
+
st.markdown("""
|
| 338 |
+
<style>
|
| 339 |
+
.stMultiSelect [data-baseweb=select] span{
|
| 340 |
+
max-width: 800px;
|
| 341 |
+
font-size: 0.9rem;
|
| 342 |
+
}
|
| 343 |
+
</style>
|
| 344 |
+
""", unsafe_allow_html=True)
|
| 345 |
+
models = st.multiselect("Please choose the models", chart_data['Model'].tolist(), default = chart_data['Model'].tolist())
|
| 346 |
|
| 347 |
if sorted == 'Ascending':
|
| 348 |
ascend = True
|
|
|
|
| 367 |
"xAxis": [
|
| 368 |
{
|
| 369 |
"type": "category",
|
| 370 |
+
"boundaryGap": True,
|
| 371 |
"triggerEvent": True,
|
| 372 |
+
"data": models,
|
| 373 |
}
|
| 374 |
],
|
| 375 |
"yAxis": [{"type": "value",
|
| 376 |
"min": min_value,
|
| 377 |
"max": max_value,
|
| 378 |
+
"boundaryGap": True
|
| 379 |
# "splitNumber": 10
|
| 380 |
}],
|
| 381 |
"series": [
|
|
|
|
| 388 |
],
|
| 389 |
}
|
| 390 |
|
| 391 |
+
# events = {
|
| 392 |
+
# "click": "function(params) { return params.value }"
|
| 393 |
+
# }
|
| 394 |
|
| 395 |
+
value = st_echarts(options=options, height="500px")
|
| 396 |
|
| 397 |
+
# if value != None:
|
| 398 |
+
# # print(value)
|
| 399 |
+
# nav_to(value)
|
| 400 |
|
| 401 |
# if value != None:
|
| 402 |
# highlight_table_line(value)
|
|
|
|
| 435 |
min_value = round(chart_data.iloc[:, 1::].min().min() - 0.1, 1)
|
| 436 |
max_value = round(chart_data.iloc[:, 1::].max().max() + 0.1, 1)
|
| 437 |
|
| 438 |
+
st.markdown("""
|
| 439 |
+
<style>
|
| 440 |
+
.stMultiSelect [data-baseweb=select] span{
|
| 441 |
+
max-width: 800px;
|
| 442 |
+
font-size: 0.9rem;
|
| 443 |
+
}
|
| 444 |
+
</style>
|
| 445 |
+
""", unsafe_allow_html=True)
|
| 446 |
+
models = st.multiselect("Please choose the models", chart_data['Model'].tolist(), default = chart_data['Model'].tolist())
|
| 447 |
+
|
| 448 |
options = {
|
| 449 |
"title": {"text": f"{category_two}"},
|
| 450 |
"tooltip": {
|
|
|
|
| 458 |
"xAxis": [
|
| 459 |
{
|
| 460 |
"type": "category",
|
| 461 |
+
"boundaryGap": True,
|
| 462 |
"triggerEvent": True,
|
| 463 |
+
"data": models,
|
| 464 |
}
|
| 465 |
],
|
| 466 |
"yAxis": [{"type": "value",
|
| 467 |
"min": min_value,
|
| 468 |
"max": max_value,
|
| 469 |
+
"boundaryGap": True
|
| 470 |
# "splitNumber": 10
|
| 471 |
}],
|
| 472 |
"series": [
|
|
|
|
| 479 |
],
|
| 480 |
}
|
| 481 |
|
| 482 |
+
# events = {
|
| 483 |
+
# "click": "function(params) { return params.value }"
|
| 484 |
+
# }
|
| 485 |
|
| 486 |
+
value = st_echarts(options=options, height="500px")
|
| 487 |
|
| 488 |
+
# if value != None:
|
| 489 |
+
# # print(value)
|
| 490 |
+
# nav_to(value)
|
| 491 |
|
| 492 |
|
| 493 |
### create table
|
|
|
|
| 514 |
data_path = f'{folder}/{category_one}/{subtitle}.csv'
|
| 515 |
chart_data = pd.read_csv(data_path).round(3)
|
| 516 |
|
| 517 |
+
st.markdown("""
|
| 518 |
+
<style>
|
| 519 |
+
.stMultiSelect [data-baseweb=select] span{
|
| 520 |
+
max-width: 800px;
|
| 521 |
+
font-size: 0.9rem;
|
| 522 |
+
}
|
| 523 |
+
</style>
|
| 524 |
+
""", unsafe_allow_html=True)
|
| 525 |
+
models = st.multiselect("Please choose the models", chart_data['Model'].tolist(), default = chart_data['Model'].tolist())
|
| 526 |
+
|
| 527 |
if sorted == 'Ascending':
|
| 528 |
ascend = True
|
| 529 |
else:
|
|
|
|
| 549 |
"xAxis": [
|
| 550 |
{
|
| 551 |
"type": "category",
|
| 552 |
+
"boundaryGap": True,
|
| 553 |
"triggerEvent": True,
|
| 554 |
+
"data": models,
|
| 555 |
}
|
| 556 |
],
|
| 557 |
"yAxis": [{"type": "value",
|
| 558 |
"min": min_value,
|
| 559 |
"max": max_value,
|
| 560 |
+
"boundaryGap": True
|
| 561 |
# "splitNumber": 10
|
| 562 |
}],
|
| 563 |
"series": [
|
|
|
|
| 599 |
"xAxis": [
|
| 600 |
{
|
| 601 |
"type": "category",
|
| 602 |
+
"boundaryGap": True,
|
| 603 |
"triggerEvent": True,
|
| 604 |
+
"data": models,
|
| 605 |
}
|
| 606 |
],
|
| 607 |
"yAxis": [{"type": "value",
|
| 608 |
"min": min_value,
|
| 609 |
"max": max_value,
|
| 610 |
# "splitNumber": 10
|
| 611 |
+
"boundaryGap": True
|
| 612 |
}],
|
| 613 |
"series": [
|
| 614 |
{
|
|
|
|
| 620 |
],
|
| 621 |
}
|
| 622 |
|
| 623 |
+
# events = {
|
| 624 |
+
# "click": "function(params) { return params.value }"
|
| 625 |
+
# }
|
| 626 |
|
| 627 |
+
value = st_echarts(options=options, height="500px")
|
| 628 |
|
| 629 |
+
# if value != None:
|
| 630 |
+
# # print(value)
|
| 631 |
+
# nav_to(value)
|
| 632 |
|
| 633 |
|
| 634 |
### create table
|