instructions
instruction-synthesizer-i1-GGUFmlfoundations-dev_-_llama3-1_8b_oh_dcft_v1_wo_unnatural_instructions-ggufmlfoundations-dev_-_llama3-1_8b_oh_v3.1_wo_unnatural_instructions-ggufat2507_-_gemma-2b-instruct-ft-python-code-instructions-ggufikea-instructions-lora-sdxlinstruction-synthesizer-GGUFmlfoundations-dev_-_oh_v1.3_unnatural_instructions_x.5-ggufmlfoundations-dev_-_oh-dcft-v1.2_no-curation_gpt-4o-mini_wo_unnatural_instructions-gguf
python_code_instructions_18k_alpaca
Dataset Card for python_code_instructions_18k_alpaca
The dataset contains problem descriptions and code in python language.
This dataset is taken from sahil2801/code_instructions_120k, which adds a prompt column in alpaca style. Refer to the source here.
natural-instructionsPreprocessed version of Super-Natural-Instructions from https://github.com/allenai/natural-instructions/tree/master/splits. The same inputs may appear with different outputs, thus to avoid duplicate inputs, you can deduplicate by the id or the inputs field.
Train Tasks:
['task001_quoref_question_generation', 'task002_quoref_answer_generation', 'task022_cosmosqa_passage_inappropriate_binary', 'task023_cosmosqa_question_generation', 'task024_cosmosqa_answer_generation'… See the full description on the dataset page: https://huggingface.co/datasets/Muennighoff/natural-instructions.code_instructions_122k_alpaca_stylehelpful-instructions
Dataset Card for Helpful Instructions
Dataset Summary
Helpful Instructions is a dataset of (instruction, demonstration) pairs that are derived from public datasets. As the name suggests, it focuses on instructions that are "helpful", i.e. the kind of questions or tasks a human user might instruct an AI assistant to perform. You can load the dataset as follows:
from datasets import load_dataset
# Load all subsets
helpful_instructions =… See the full description on the dataset page: https://huggingface.co/datasets/HuggingFaceH4/helpful-instructions.sec-contracts-financial-extraction-instructions
S&P 500 SEC Financial Extraction Instructions
Dataset Summary
7,683 instruction-tuning examples for training LLMs to extract structured financial data from SEC filings. Covers two filing types across S&P 500 companies:
Split
Examples
Filing Type
Description
train
3,430
Exhibit 10 + DEF 14A
Positive examples with validated outputs
corrective
4,253
Exhibit 10 + DEF 14A
Corrective, rescued, and negative examples
Exhibit 10 — Material Contracts (2… See the full description on the dataset page: https://huggingface.co/datasets/TheTokenFactory/sec-contracts-financial-extraction-instructions.Malay-Dialect-Instructions
Malay dialect instruction including coding
Negeri Sembilan
QA
public transport QA,
Coding
CUDA coding,
Kedah
QA
infra QA,
Coding
Rust coding,
Kelantan
QA
Najib Razak QA,
Coding
Go coding,
Perak
QA
Anwar Ibrahim QA,
Coding
SQL coding,
Pahang
QA
Pendatang asing QA,
Coding
Typescript coding,
Terengganu… See the full description on the dataset page: https://huggingface.co/datasets/mesolitica/Malay-Dialect-Instructions.