matlok - Python Copilot Image Datasets
					Collection
				
More extracted images on github: https://github.com/matlok-ai/python-copilot-image-and-audio-examples/tree/main/png
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				4 items
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| filename
				 stringlengths 20 55 | repo
				 stringclasses 1
				value | path
				 stringlengths 88 141 | dbytes
				 unknown | dbytes_len
				 int64 368k 1.63M | dbytes_mb
				 float64 0.35 1.55 | type
				 stringclasses 1
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				 int64 0 0 | 
|---|---|---|---|---|---|---|---|
| 
	image.func.masked_run_glue.png | 
	H2O | "H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/movement-pruning/imag(...TRUNCATED) | "iVBORw0KGgoAAAANSUhEUgAADnQAAA50CAYAAABW00Z8AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiw(...TRUNCATED) | 655,026 | 0.62 | 
	png | 0 | 
| 
	image.func.counts_parameters.png | 
	H2O | "H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/movement-pruning/imag(...TRUNCATED) | "iVBORw0KGgoAAAANSUhEUgAADOQAAAzkCAYAAABF7XA+AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiw(...TRUNCATED) | 386,499 | 0.37 | 
	png | 0 | 
| 
	image.func.utils.png | 
	H2O | "H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/lxmert/image.func.uti(...TRUNCATED) | "iVBORw0KGgoAAAANSUhEUgAAD6AAAA+gCAYAAADuf+MCAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiw(...TRUNCATED) | 1,070,163 | 1.02 | 
	png | 0 | 
| 
	image.func.extracting_data.png | 
	H2O | "H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/lxmert/image.func.ext(...TRUNCATED) | "iVBORw0KGgoAAAANSUhEUgAADOQAAAzkCAYAAABF7XA+AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiw(...TRUNCATED) | 375,932 | 0.36 | 
	png | 0 | 
| 
	image.func.processing_image.png | 
	H2O | "H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/lxmert/image.func.pro(...TRUNCATED) | "iVBORw0KGgoAAAANSUhEUgAADOQAAAzkCAYAAABF7XA+AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiw(...TRUNCATED) | 397,731 | 0.38 | 
	png | 0 | 
| 
	image.func.modeling_frcnn.png | 
	H2O | "H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/lxmert/image.func.mod(...TRUNCATED) | "iVBORw0KGgoAAAANSUhEUgAAD6AAAA+gCAYAAADuf+MCAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiw(...TRUNCATED) | 1,119,477 | 1.07 | 
	png | 0 | 
| 
	image.func.modeling_flax_performer_utils.png | 
	H2O | "H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/performer/image.func.(...TRUNCATED) | "iVBORw0KGgoAAAANSUhEUgAADnQAAA50CAYAAABW00Z8AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiw(...TRUNCATED) | 821,034 | 0.78 | 
	png | 0 | 
| 
	image.func.run_mlm_performer.png | 
	H2O | "H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/performer/image.func.(...TRUNCATED) | "iVBORw0KGgoAAAANSUhEUgAADnQAAA50CAYAAABW00Z8AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiw(...TRUNCATED) | 670,569 | 0.64 | 
	png | 0 | 
| 
	image.func.train_complexity_predictor.png | 
	H2O | "H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/codeparrot/examples/i(...TRUNCATED) | "iVBORw0KGgoAAAANSUhEUgAADOQAAAzkCAYAAABF7XA+AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiw(...TRUNCATED) | 425,846 | 0.41 | 
	png | 0 | 
| 
	image.func.minhash_deduplication.png | 
	H2O | "H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/codeparrot/scripts/im(...TRUNCATED) | "iVBORw0KGgoAAAANSUhEUgAADnQAAA50CAYAAABW00Z8AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiw(...TRUNCATED) | 774,585 | 0.74 | 
	png | 0 | 
This dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.
Each row contains a png file in the dbytes column.
The png is in the dbytes column:
{
    "dbytes": "binary",
    "dbytes_len": "int64",
    "dbytes_mb": "float64",
    "filename": "string",
    "path": "string",
    "repo": "string",
    "type": "string"
}
from datasets import load_dataset
ds = load_dataset("matlok/python-image-copilot-training-using-function-knowledge-graphs", data_dir="files")