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Error code: ConfigNamesError Exception: DataFilesNotFoundError Message: No (supported) data files found in ebowwa/relative-postioning Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 73, in compute_config_names_response config_names = get_dataset_config_names( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names dataset_module = dataset_module_factory( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1904, in dataset_module_factory raise e1 from None File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1885, in dataset_module_factory return HubDatasetModuleFactoryWithoutScript( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1270, in get_module module_name, default_builder_kwargs = infer_module_for_data_files( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 597, in infer_module_for_data_files raise DataFilesNotFoundError("No (supported) data files found" + (f" in {path}" if path else "")) datasets.exceptions.DataFilesNotFoundError: No (supported) data files found in ebowwa/relative-postioning
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NOTE: this is a huggingface duplicate for further processing. Here's the originial readme
Dataset Card for Dataset Name
This dataset aims to teach LLMs relative positioning (e.g. above, left from, below, etc.), which in my findings most LLMs, even SOTA where not able to produce under all circumstances. Will be pushing a fine-tuned mixtral-7x8B with this dataset.
Dataset Details
Dataset Description
Contains Data for relative positioning on a grid(256, 256). Assumes Origin [0, 0] is in the bottom left. Two Objects (Object 1, Object 2) are randomly created. Answer is there relative position to one another.
- Curated by: [Antoine Angert]
- Language(s) (NLP): [English]
- License: [apache-2.0]
Uses
Direct Use
Can be used to fine-tune Language Models. (Althought so far not been tested, will update)
Dataset Structure
Features: Prompt(String), Response(String)
Dataset Creation
Curation Rationale
I did some testing to see how well LLMs are able to handle positional data(2D, 3D). I found that most small models (tested: llama-7B, llama-13B, mistral-7B) have very poor positional understanding. Most bigger Models (tested: gpt-3.5-turbo, gpt-4, llama-70B, mixtral-7x8B) have a fairly good positional understanding, as long as no other context is provided. When I tried using positional reasoning with some other unrelated context, the performance of these bigger models dropped imensly. This is my first attempt of trying to embed this understanding directly into the models and not throught context.
Data Collection and Processing
The dataset was generated using a python script.
Dataset Card Authors [optional]
Antoine Angert
Dataset Card Contact
Contact under: antoine.angert@hsbi.de
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