upload_ckpt

README.md

@@ -3,10 +3,11 @@ title: PyABSA ATEPC
 emoji: 📈
 colorFrom: purple
 colorTo: yellow
-sdk: gradio
-sdk_version: 2.8.14
 app_file: app.py
 pinned: false
+sdk: gradio
+sdk_version: 3.0.24
+license: mit
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference

app.py

@@ -0,0 +1,93 @@
+import os
+import random
+import gradio as gr
+import pandas as pd
+import requests
+
+from pyabsa import ATEPCCheckpointManager
+from pyabsa.functional.dataset.dataset_manager import download_datasets_from_github, ABSADatasetList, detect_infer_dataset
+
+download_datasets_from_github(os.getcwd())
+
+dataset_items = {dataset.name: dataset for dataset in ABSADatasetList()}
+
+URL = 'https://api.visitorbadge.io/api/combined?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2Fyangheng%2Fpyabsa_inference&label=Inference%20Count&labelColor=%2337d67a&countColor=%23f47373&style=flat&labelStyle=none'
+
+def get_example(dataset):
+    task = 'apc'
+    dataset_file = detect_infer_dataset(dataset_items[dataset], task)
+
+    for fname in dataset_file:
+        lines = []
+        if isinstance(fname, str):
+            fname = [fname]
+
+        for f in fname:
+            print('loading: {}'.format(f))
+            fin = open(f, 'r', encoding='utf-8')
+            lines.extend(fin.readlines())
+            fin.close()
+        for i in range(len(lines)):
+            lines[i] = lines[i][:lines[i].find('!sent!')].replace('[ASP]', '')
+        return sorted(set(lines), key=lines.index)
+
+
+dataset_dict = {dataset.name: get_example(dataset.name) for dataset in ABSADatasetList()}
+aspect_extractor = ATEPCCheckpointManager.get_aspect_extractor(checkpoint='multilingual-256-2')
+
+
+def perform_inference(text, dataset):
+    if not text:
+        text = dataset_dict[dataset][random.randint(0, len(dataset_dict[dataset]) - 1)]
+
+    result = aspect_extractor.extract_aspect(inference_source=[text],
+                                             pred_sentiment=True)
+
+    result = pd.DataFrame({
+        'aspect': result[0]['aspect'],
+        'sentiment': result[0]['sentiment'],
+        # 'probability': result[0]['probs'],
+        'confidence': [round(x, 4) for x in result[0]['confidence']],
+        'position': result[0]['position']
+    })
+    requests.get(URL)
+    return result, '{}'.format(text)
+
+
+demo = gr.Blocks()
+
+with demo:
+    gr.Markdown("# <p align='center'>Multilingual Aspect-based Sentiment Analysis !</p>")
+    gr.Markdown("""### Repo: [PyABSA](https://github.com/yangheng95/PyABSA)
+                ### Author: [Heng Yang](https://github.com/yangheng95) (杨恒)
+                [![Downloads](https://pepy.tech/badge/pyabsa)](https://pepy.tech/project/pyabsa) 
+                [![Downloads](https://pepy.tech/badge/pyabsa/month)](https://pepy.tech/project/pyabsa)
+                """
+                )
+    gr.Markdown("Your input text should be no more than 80 words, that's the longest text we used in training. However, you can try longer text in self-training ")
+    gr.Markdown("**You don't need to split each Chinese (Korean, etc.) token as the provided, just input the natural language text.**")
+    gr.Markdown("请确保输入的文本长度不超过200词，这是训练时的最大文本长度，过长将不会获得结果")
+    gr.Markdown("**提供的中文等其他非拉丁语系数据集采用了空格分字，这是早期数据集的遗留问题，预测时不用对中文等语言进行空格分字**")
+    output_dfs = []
+    with gr.Row():
+        with gr.Column():
+            input_sentence = gr.Textbox(placeholder='Leave this box blank and choose a dataset will give you a random example...', label="Example:")
+            gr.Markdown("You can find the datasets at [github.com/yangheng95/ABSADatasets](https://github.com/yangheng95/ABSADatasets/tree/v1.2/datasets/text_classification)")
+            dataset_ids = gr.Radio(choices=[dataset.name for dataset in ABSADatasetList()[:-1]], value='Laptop14', label="Datasets")
+            inference_button = gr.Button("Let's go!")
+            gr.Markdown("There is a [demo](https://huggingface.co/spaces/yangheng/PyABSA-ATEPC-Chinese) specialized for the Chinese langauge")
+            gr.Markdown("This demo support many other language as well, you can try and explore the results of other languages by yourself.")
+
+        with gr.Column():
+            output_text = gr.TextArea(label="Example:")
+            output_df = gr.DataFrame(label="Prediction Results:")
+            output_dfs.append(output_df)
+
+        inference_button.click(fn=perform_inference,
+                               inputs=[input_sentence, dataset_ids],
+                               outputs=[output_df, output_text])
+
+    gr.Markdown("![visitor badge](https://visitor-badge.glitch.me/badge?page_id=https://huggingface.co/spaces/yangheng/Multilingual-Aspect-Based-Sentiment-Analysis)")
+    gr.Markdown("![Visitors]({})".format(URL))
+
+demo.launch(share=True)

checkpoint-v1.16.json

@@ -0,0 +1,634 @@
+{
+  "1.16.0+": {
+    "APC": {
+      "english": {
+        "id": "https://drive.google.com/file/d/1JIFhaAdoCeZI5CQqfOix3pnrYa6_Mf9S/view?usp=sharing",
+        "Training Model": "FAST-LSA-S",
+        "Training Dataset": "English",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.6.3+",
+        "Checkpoint File": "fast_lsa_s_acc_84.9_f1_82.11.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "chinese": {
+        "id": "https://drive.google.com/file/d/1B0RHazOCm2eOWLWExQkeapHr9d3OiZl7/view?usp=sharing",
+        "Training Model": "FAST-LCF-MDeBERTa",
+        "Training Dataset": "Chinese",
+        "Language": "Chinese",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.8.2+",
+        "Checkpoint File": "fast_lcf_bert_Chinese_acc_97.11_f1_96.54.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "multilingual": {
+        "id": "https://drive.google.com/file/d/15ls1hcGvk27UnfMsXZtk780h7tTBbNws/view?usp=sharing",
+        "Training Model": "FAST-LCF-Deberta",
+        "Training Dataset": "Multilingual",
+        "Language": "Multilingual",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.8.2+",
+        "Checkpoint File": "fast_lcf_bert_Multilingual_acc_94.72_f1_90.07.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "multilingual2": {
+        "id": "https://drive.google.com/file/d/1YCYKpEnff-DBUHd-8vWmgsnng5ZT_2cs/view?usp=sharing",
+        "Training Model": "FAST-LCF-Deberta",
+        "Training Dataset": "Multilingual",
+        "Language": "Multilingual",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.10.5+",
+        "Checkpoint File": "fast_lsa_t_v2_Multilingual_acc_88.44_f1_82.66.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "dlcf-dca-bert1": {
+        "id": "https://drive.google.com/file/d/1w-NtWujPglsvZu4-jC6Vmu8Iz8CvX-1u/view?usp=sharing",
+        "Training Model": "dlcf-dca-bert",
+        "Training Dataset": "Laptop 14",
+        "Language": "English",
+        "Description": "Trained on T4",
+        "Available Version": "1.1.17-1.1.23",
+        "Author": "M, Xu ([email protected])"
+      },
+      "dlcf-dca-bert2": {
+        "id": "https://drive.google.com/file/d/1w-NtWujPglsvZu4-jC6Vmu8Iz8CvX-1u/view?usp=sharing",
+        "Training Model": "dlcf-dca-bert",
+        "Training Dataset": "Restaurant 14",
+        "Language": "English",
+        "Description": "Trained on T4",
+        "Available Version": "1.1.17-1.1.23",
+        "Author": "M, Xu ([email protected])"
+      },
+      "HELP-WANTED": {
+        "id": "",
+        "Description": "You can help us by sharing checkpoints (e.g. models trained on you own datasets) with community.",
+        "Checkpoint File": "PLEASE NOTE THAT THIS IS NOT A REAL CHECKPOINT!",
+        "Available Version": ""
+      }
+    },
+    "ATEPC": {
+      "english": {
+        "id": "",
+        "Training Model": "FAST-LCFS-ATEPC",
+        "Training Dataset": "English",
+        "Language": "English",
+        "Description": "Trained on RTX3090, this checkpoint use bert-spc in ATEPC training",
+        "Available Version": "1.16.0+",
+        "Checkpoint File": "fast_lcf_atepc_English_cdw_apcacc_85.4_apcf1_82.53_atef1_80.19.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "chinese": {
+        "id": "",
+        "Training Model": "FAST-LCF-ATEPC",
+        "Training Dataset": "Chinese",
+        "Language": "Chinese",
+        "Description": "Trained on RTX3090 BERT-BASE-CHINESE",
+        "Available Version": "1.16.0+",
+        "Checkpoint File": "fast_lcf_atepc_Chinese_cdw_apcacc_96.09_apcf1_95.14_atef1_83.69.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "multilingual": {
+        "id": "",
+        "Training Model": "FAST-LCF-ATEPC",
+        "Training Dataset": "ABSADatasets.Multilingual",
+        "Language": "Multilingual",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.16.0+",
+        "Checkpoint File": "fast_lcf_atepc_Multilingual_cdw_apcacc_86.76_apcf1_79.78_atef1_78.03.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "multilingual-256": {
+        "id": "",
+        "Training Model": "FAST-LCF-ATEPC",
+        "Training Dataset": "ABSADatasets.Multilingual",
+        "Language": "Multilingual",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.16.0+",
+        "Checkpoint File": "fast_lcf_atepc_Multilingual_cdw_apcacc_87.09_apcf1_79.95_atef1_75.55.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "multilingual-256-2": {
+        "id": "",
+        "Training Model": "FAST-LCF-ATEPC",
+        "Training Dataset": "ABSADatasets.Multilingual",
+        "Language": "Multilingual",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.16.0+",
+        "Checkpoint File": "fast_lcf_atepc_Multilingual_cdw_apcacc_86.68_apcf1_80.63_atef1_75.15.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "HELP-WANTED": {
+        "id": "",
+        "Description": "You can help us by sharing checkpoints (e.g. models trained on you own datasets) with community.",
+        "Checkpoint File": "PLEASE NOTE THAT THIS IS NOT A REAL CHECKPOINT!",
+        "Available Version": ""
+      }
+    },
+    "TC": {
+      "tc-sst2": {
+        "id": "https://drive.google.com/file/d/1KgEB7MJ8bjrBiYdbtiojreeYegnUtq51/view?usp=sharing",
+        "Training Model": "TAD",
+        "Training Dataset": "SST2",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TC-SST2.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tc-agnews10k": {
+        "id": "https://drive.google.com/file/d/1JiRL19maSBiu9_1VBpP1gMwN8qkZsAtC/view?usp=sharing",
+        "Training Model": "TAD",
+        "Training Dataset": "AGNews",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TC-AGNews10K.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tc-imdb10k": {
+        "id": "https://drive.google.com/file/d/1TD0xyKKEfs_S0Ze0EmEb16Eq5pdukjN_/view?usp=sharing",
+        "Training Model": "TAD",
+        "Training Dataset": "IMDB10K",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TC-IMDB10K.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "HELP-WANTED": {
+        "id": "",
+        "Description": "You can help us by sharing checkpoints (e.g. models trained on you own datasets) with community.",
+        "Checkpoint File": "PLEASE NOTE THAT THIS IS NOT A REAL CHECKPOINT!",
+        "Available Version": ""
+      }
+    },
+    "TAD": {
+      "tad-sst2": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "SST2",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-SST2.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tad-bert-sst2": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "SST2",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-BERT-SST2.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tad-sst2bae": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "SST2",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-SST2BAE.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tad-sst2pwws": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "SST2",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-SST2PWWS.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tad-sst2textfooler": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "SST2",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-SST2TextFooler.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tad-agnews10k": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "AGNews",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-AGNews10K.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tad-bert-agnews10k": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "AGNews",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-BERT-AGNews10K.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tad-agnews10kbae": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "AGNews",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-AGNews10KBAE.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tad-agnews10kpwws": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "AGNews",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-AGNews10KPWWS.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tad-agnews10ktextfooler": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "AGNews",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-AGNews10KTextFooler.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tad-amazon": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "AGNews",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-Amazon.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tad-bert-amazon": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "AGNews",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-Amazon-BERT.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tad-amazonbae": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "AGNews",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-AmazonBAE.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tad-amazonpwws": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "AGNews",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-AmazonPWWS.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "tad-amazontextfooler": {
+        "id": "",
+        "Training Model": "TAD",
+        "Training Dataset": "AGNews",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.15+",
+        "Checkpoint File": "TAD-AmazonTextFooler.zip",
+        "Author": "H, Yang ([email protected])"
+      }
+    }
+  },
+  "1.0.0-1.15.7": {
+    "APC": {
+      "english": {
+        "id": "https://drive.google.com/file/d/1JIFhaAdoCeZI5CQqfOix3pnrYa6_Mf9S/view?usp=sharing",
+        "Training Model": "FAST-LSA-S",
+        "Training Dataset": "English",
+        "Language": "English",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.6.3+",
+        "Checkpoint File": "fast_lsa_s_acc_84.9_f1_82.11.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "chinese": {
+        "id": "https://drive.google.com/file/d/1B0RHazOCm2eOWLWExQkeapHr9d3OiZl7/view?usp=sharing",
+        "Training Model": "FAST-LCF-MDeBERTa",
+        "Training Dataset": "Chinese",
+        "Language": "Chinese",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.8.2+",
+        "Checkpoint File": "fast_lcf_bert_Chinese_acc_97.11_f1_96.54.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "multilingual": {
+        "id": "https://drive.google.com/file/d/15ls1hcGvk27UnfMsXZtk780h7tTBbNws/view?usp=sharing",
+        "Training Model": "FAST-LCF-Deberta",
+        "Training Dataset": "Multilingual",
+        "Language": "Multilingual",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.8.2+",
+        "Checkpoint File": "fast_lcf_bert_Multilingual_acc_94.72_f1_90.07.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "multilingual2": {
+        "id": "https://drive.google.com/file/d/1YCYKpEnff-DBUHd-8vWmgsnng5ZT_2cs/view?usp=sharing",
+        "Training Model": "FAST-LCF-Deberta",
+        "Training Dataset": "Multilingual",
+        "Language": "Multilingual",
+        "Description": "Trained on RTX3090",
+        "Available Version": "1.10.5+",
+        "Checkpoint File": "fast_lsa_t_v2_Multilingual_acc_88.44_f1_82.66.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "dlcf-dca-bert1": {
+        "id": "https://drive.google.com/file/d/1w-NtWujPglsvZu4-jC6Vmu8Iz8CvX-1u/view?usp=sharing",
+        "Training Model": "dlcf-dca-bert",
+        "Training Dataset": "Laptop 14",
+        "Language": "English",
+        "Description": "Trained on T4",
+        "Available Version": "1.1.17-1.1.23",
+        "Author": "M, Xu ([email protected])"
+      },
+      "dlcf-dca-bert2": {
+        "id": "https://drive.google.com/file/d/1w-NtWujPglsvZu4-jC6Vmu8Iz8CvX-1u/view?usp=sharing",
+        "Training Model": "dlcf-dca-bert",
+        "Training Dataset": "Restaurant 14",
+        "Language": "English",
+        "Description": "Trained on T4",
+        "Available Version": "1.1.17-1.1.23",
+        "Author": "M, Xu ([email protected])"
+      },
+      "HELP-WANTED": {
+        "id": "",
+        "Description": "You can help us by sharing checkpoints (e.g. models trained on you own datasets) with community.",
+        "Checkpoint File": "PLEASE NOTE THAT THIS IS NOT A REAL CHECKPOINT!",
+        "Available Version": ""
+      }
+    },
+    "ATEPC": {
+      "english": {
+        "id": "https://drive.google.com/file/d/1_oBCLi_bjs4CxmEXfVIw8qZCmbJvr-PE/view?usp=sharing",
+        "Training Model": "FAST-LCFS-ATEPC",
+        "Training Dataset": "English",
+        "Language": "English",
+        "Description": "Trained on RTX3090, this checkpoint use bert-spc in ATEPC training",
+        "Available Version": "1.8.4-1.15.7",
+        "Checkpoint File": "fast_lcf_atepc_English_cdw_apcacc_85.03_apcf1_82.76_atef1_84.8.zip",
+        "Author": "H, Yang ([email protected])"
+      },
+      "chinese": {
+        "id": "https://drive.google.com/file/d/1wHlEeKbQg51LEgr-J353HQhyPgPDEMrp/view?usp=sharing",
+        "Training Model": "FAST-LCF-ATEPC",
+        "Training Dataset": "Chinese",
+        "Language": "Chinese",
+        "Description": "Trained on RTX3090 BERT-BASE-CHINESE",
+        "Available Version": "1.8.4-1.15.7",
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