datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Stable-diffusion-configstaboo-leaf
taboo-leaf
This dataset contains conversational data in JSONL format, suitable for Supervised Fine-Tuning (SFT).
Usage
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("bcywinski/taboo-leaf")
Format
The dataset is in JSONL format where each line contains a conversation record suitable for training chat models.
plant-pet-toxicity-database
PlantFun Plant-Pet Toxicity Database
This dataset is exported from the GitHub Repository.
Official website: plantfun.app.
Snapshot
Generated at: 2026-02-13T02:09:58Z
Total markdown articles: 1313
Pet Toxicity Reports: 498
Misdiagnosis Case Studies: 408
Dynamic Care Protocols: 407
Detailed Encyclopedia: Explore all 1313 plants on PlantFun
Files
../articles.csv
../articles.jsonl
../manifest.json
Suggested usage
Plant toxicity and pet safety… See the full description on the dataset page: https://huggingface.co/datasets/LeafVibe/plant-pet-toxicity-database.adaption-crop-disease-leaf-images
This dataset is a remastered version of this dataset prepared using Adaption's Adaptive Data platform.
adaption-crop_disease_leaf_images
This dataset contains image-based samples for identifying various crop diseases affecting plants such as apples, corn, tomatoes, and rice. Each entry consists of a prompt requesting disease identification and a completion specifying the diagnosed condition, including healthy states. The data is formatted as prompt-completion pairs suitable for… See the full description on the dataset page: https://huggingface.co/datasets/RatnambarBaghel/adaption-crop-disease-leaf-images.leafly-full-dump-cannabisBean-Leaf-Detection-Dataset
Bean Leaf Detection Dataset
The current agricultural sector faces the challenge of crop pest and disease detection. Due to the lack of efficient and accurate detection technologies, crops suffer severe losses. Existing solutions often rely on manual detection, which is not only inefficient but also prone to errors. The Bean Leaf Detection Dataset aims to provide high-quality annotated image data to help researchers and developers develop more precise computer vision algorithms to… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Bean-Leaf-Detection-Dataset.adaption-crop-disease-leaf-images-v1
This dataset is a remastered version of this dataset prepared using Adaption's Adaptive Data platform.
adaption-crop_disease_leaf_images
This dataset contains image-based samples for identifying various crop diseases affecting plants such as apples, corn, tomatoes, and rice. Each entry consists of a prompt requesting disease identification and a completion specifying the diagnosed condition, including healthy states. The data is formatted as prompt-completion pairs suitable for… See the full description on the dataset page: https://huggingface.co/datasets/RatnambarBaghel/adaption-crop-disease-leaf-images-v1.leafspark__Llama-3.1-8B-MultiReflection-Instruct-details
Dataset Card for Evaluation run of leafspark/Llama-3.1-8B-MultiReflection-Instruct
Dataset automatically created during the evaluation run of model leafspark/Llama-3.1-8B-MultiReflection-Instruct
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/leafspark__Llama-3.1-8B-MultiReflection-Instruct-details.leafdatarubao_point_normalincotel-simchat-dataset
SimChat Dialogues Dataset
Author: leafstudiosDotLicense: Incotelligence License (see LICENSE.md)
Description
This dataset contains ~500 lines of short chatbot dialogues for the experimental chatbot SimChat (Incotelligence).Format:
C: = user input
S: = expected chatbot response
Example
C: Hello
S: Hi!
C: How are you?
S: I'm fine, thank you for asking!
Converted JSONL format for Hugging Face:
{"prompt": "Hello", "response": "Hi!"}
{"prompt": "How are you?"… See the full description on the dataset page: https://huggingface.co/datasets/leafstudiosDot/incotel-simchat-dataset.