datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
reasoning-persona-dataset_test
Reasoning + Persona SFT Dataset
Columns: instruction, input, output, persona, reasoning_summaryUse: Supervised fine-tuning for cinematic/storytelling or creative-director style outputs.
Schema
instruction (str)
input (str)
output (str)
persona (str)
reasoning_summary (str, brief rationale cue)
Citation
Author: saravan
qwen3.5_test_data
Testing the Blind Spots of Qwen3.5-0.8B-Base Model:
Model Tested: Qwen/Qwen3.5-0.8B-Base
Installation of necessary libraries
pip -q install -U transformers accelerate
How the Model Was Loaded
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
MODEL_NAME = "Qwen/Qwen3.5-0.8B-Base"
data_type = torch.bfloat16 if torch.cuda.is_available() else torch.float32
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, trust_remote_code=True)
model =… See the full description on the dataset page: https://huggingface.co/datasets/rileydrizzy/qwen3.5_test_data.TRObject-Dataset-Test
TRObject Code Generation Instruction Dataset
This dataset contains natural language instructions paired with TRObject code outputs.
It was created for fine-tuning and evaluating domain-specific LLMs that generate TRObject code for Clomosy-style mobile application development.
Dataset Description
TRObject is used in the Clomosy mobile application development platform. Since general-purpose LLMs do not reliably understand TRObject syntax or Clomosy-specific UI patterns… See the full description on the dataset page: https://huggingface.co/datasets/odenmehmet/TRObject-Dataset-Test.test-datadataset_for_testtestdataset2