datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
upvoteweb-posts
upvoteweb: posts
Posts in upvoteweb.
configs
[!IMPORTANT]There are several configs representing different permutations of this dataset. Load the relevant config for the task you are interested in.
Overview of configs:
default: largely unfiltered/unprocessed original data
eduscored: the "eduscore" predicted on the text column with huggingface's trained classifier
en-clean: filter language for en and language_score for > 0.6. Run clean-text on the text col, preserving… See the full description on the dataset page: https://huggingface.co/datasets/BEE-spoke-data/upvoteweb-posts.BeejX-Agriculture-DAPT-CorpusBeejX LLM: DAPT Corpus
Curating ""Grade A+ Clean Text for Indian Agriculture AI.
Dataset Overview
The BeejX DAPT Corpus (dapt_train_final.txt) is a highly curated Domain-Adapted Pre-Training (DAPT) dataset designed to teach Large Language Models the deep, technical nuances of Indian Agriculture.
Our goal was to transform raw, noisy agricultural documents (textbooks, market reports, scientific PDFs) into "Grade A+" clean text suitable for continuously training base models… See the full description on the dataset page: https://huggingface.co/datasets/bf369/BeejX-Agriculture-DAPT-Corpus.ogiri-bokete-unsloth-vlm
Japanese Bokete Ogiri — Unsloth VLM format
YANS-official/ogiri-bokete を、UnslothのVision SFTで扱える会話形式に変換した非公開用データセットです。
各JSONLレコードは「1画像 + 1回答」です。
{
"messages": [
{"role": "user", "content": [
{"type": "image", "image": "images/124469.jpg"},
{"type": "text", "text": "この画像のお題に対して、面白い一言を1つ返してください。"}
]},
{"role": "assistant", "content": [
{"type": "text", "text": "..."}
]}
]
}
Files
train.jsonl: 1,678 records / 630 prompts… See the full description on the dataset page: https://huggingface.co/datasets/beezza/ogiri-bokete-unsloth-vlm.kenya-bee-health-qa-image-triples
Kenya Bee Health Training Data
This folder is a starter database for BeeCare Anywhere / Gemma Apiary. It is intentionally small, transparent, and license-aware: use it to prove the Q/A/image-triple pipeline, then expand it with Kenyan field data before trusting model behavior in production.
Important Model Note
google/gemma-2b is a text-to-text, decoder-only model. It cannot directly read pictures. Use these image triples with a vision-capable model path, for… See the full description on the dataset page: https://huggingface.co/datasets/yahelr1/kenya-bee-health-qa-image-triples.beecare-vision-public-bilingual-train
BeeCare Vision Public Bilingual Train
Default train split for Unsloth vision fine-tuning. Each row has image, messages, and metadata.
Use in Unsloth Studio as: yahelr1/beecare-vision-public-bilingual-train.
beecare-vision-rich-qa-bilingual
BeeCare Vision Rich QA Bilingual
Unsloth-friendly rich image dataset. Default split is train. Columns include image, text, question, answer, condition_label, task, severity, and safety/provenance fields.
In Unsloth, select this repo and map image to image, text to text if asked.