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README.md

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+---
+license:
+- other
+pretty_name: >-
+  python copilot image training using import knowledge graphs
+dataset_info:
+- config_name: view_schema
+  splits:
+  - name: schema
+configs:
+- config_name: view_schema
+  data_files:
+  - split: view_schema
+    path: files/lok-python-copilot-img.import-v1_00000780.parquet
+size_categories:
+- 100K<n<1M
+tags:
+- python-copilot
+- python-coding
+- python-architecture
+- knowledge-graphs
+- multimodal
+- text-image-audio
+- fine-tuning
+- training
+- question-answering
+- image-knowledge-graph
+- alpaca
+- mp3
+- png
+- text
+- instruct
+- import
+- imports
+# supported task_categories
+# text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, conversational, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, other
+task_categories:
+- text-to-image
+- image-to-image
+- question-answering
+# supported task_ids
+# acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-generation, dialogue-modeling, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering
+task_ids:
+- parsing
+---
+
+## Python Copilot Image Training using Import Knowledge Graphs
+
+This dataset is a subset of the matlok python copilot datasets. Please refer to the [Multimodal Python Copilot Training Overview](https://huggingface.co/datasets/matlok/multimodal-python-copilot-training-overview) for more details on how to use this dataset.
+
+### Details
+
+Each row contains a png file in the **dbytes** column.
+
+- Rows: 216642
+- Size: 211.2 GB
+- Data type: png
+- Format: Knowledge graph using NetworkX with alpaca text box
+
+### Schema
+
+The png is in the **dbytes** column:
+
+```
+{
+    "dbytes": "binary",
+    "dbytes_len": "int64",
+    "dbytes_mb": "float64",
+    "filename": "string",
+    "path": "string",
+    "repo": "string",
+    "type": "string"
+}
+```
+
+### How to use the dataset
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("matlok/python-image-copilot-training-using-import-knowledge-graphs", data_dir="files")
+```
+