datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
r9-research-framework
R9 Research Framework — Qwen3.5-9B Distillation
⚠️ CRITICAL: READ FIRST — Ollama Inference Flag Required
If you serve any Qwen3.5-derived model from this lineage via Ollama,
you MUST pass "think": false in the /api/chat request body.
curl -X POST http://localhost:11434/api/chat \
-d '{"model": "qwen3.5-9b-r10:q4km", "think": false, "messages": [...], "stream": false}'
Without this flag the model will appear to "loop" and produce empty answers
on 25-46% of requests.… See the full description on the dataset page: https://huggingface.co/datasets/cudabenchmarktest/r9-research-framework.grounded-behavior-framework-v1_5
Grounded Behavior Framework N1 v1.5
Dataset sintético em português europeu para treino e avaliação de respostas
fundamentadas num contexto fornecido. Cada exemplo contém um contexto, uma
pergunta e uma resposta curta que aparece literalmente no contexto.
Como carregar
from datasets import load_dataset
dataset = load_dataset("empgces/grounded-behavior-framework-v1_5")
print(dataset)
print(dataset["train"][0])
Splits
Split
Exemplos
Utilização… See the full description on the dataset page: https://huggingface.co/datasets/empgces/grounded-behavior-framework-v1_5.Prettybird-Framework
🚀 The Future Standard / Geleceğin Standartı
[English]
Beyond Raw Data: The Behavioral Revolution
The AI industry has been obsessed with the volume of data. At Prometech A.Ş., we are shifting the focus to the process of thought. BCE-Prettybird-Micro-Standart is not just a collection of Q&As; it is a blueprint for behavioral reasoning. By integrating Path Mapping and Behavioral DNA into the training loop, we are setting the new industry standard: Small models with elite… See the full description on the dataset page: https://huggingface.co/datasets/pthinc/Prettybird-Framework.sft-mobile-query-framework
SFT Mobile Query Framework Dataset
Dataset Description
This dataset contains 3607 training pairs for supervised fine-tuning (SFT) of language models to parse natural language queries about mobile phones into structured JSON execution plans.
Dataset Summary
Total Examples: 3607
Format: JSONL (question-answer pairs)
Task: Query Parsing & Structured Output Generation
Domain: Mobile Phone Specifications
Language: English
Purpose
This dataset is… See the full description on the dataset page: https://huggingface.co/datasets/sujitpandey/sft-mobile-query-framework.amber-framework-knowledge-pack
Amber Framework Knowledge Pack (demo)
The demo knowledge pack dataset behind
AgentC-Consulting/knowledge-packs:
teach a small local model the Amber web framework (Crystal),
and measure whether it learned anything with a before/after eval harness.
A knowledge pack compiles a body of expertise into curated sources, schema-validated
generated training JSONL, a contamination-guarded held-out eval set, and a JSON manifest.
This repo ships the exact training data and the two 50-item… See the full description on the dataset page: https://huggingface.co/datasets/crimson-knight/amber-framework-knowledge-pack.