datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
IF-multi-constraints-upto5-LFM2.5-prompts
IF_multi_constraints_upto5 → LFM2.5 prompt format (for RLVR / rejection sampling / DPO)
A derivative of allenai/IF_multi_constraints_upto5 (odc-by)
normalized for fine-tuning Liquid AI LFM2 / LFM2.5 models, whose native tool-call format is Pythonic:
<|im_start|>assistant
<|tool_call_start|>[get_weather(location='Paris, France', unit='celsius')]<|tool_call_end|><|im_end|>
Prompt-only rows (prompt_only = true): Tulu-SFT instructions with up to 5 verifiable constraints from IFEval… See the full description on the dataset page: https://huggingface.co/datasets/hungbenjamin402/IF-multi-constraints-upto5-LFM2.5-prompts.reasoning-sft-IF_multi_constraints_upto5
reasoning-sft-IF_multi_constraints_upto5
Instruction-following dataset with multi-constraint prompts (up to 5 constraints), paired with reasoning responses generated.
Format
Each row has three columns:
input — list of dicts [{"role": "user", "content": "..."}, ...]
response — model response string (includes <think> reasoning block)
category — constraint category label
Usage
import random
import pyarrow.parquet as pq
from huggingface_hub import hf_hub_download… See the full description on the dataset page: https://huggingface.co/datasets/AmanPriyanshu/reasoning-sft-IF_multi_constraints_upto5.IF_multi_constraints_upto5_safe
IF_multi_constraints_upto5 (safety filtered)
A drop-in replacement for allenai/IF_multi_constraints_upto5
with prompts that Qwen/Qwen3Guard-Gen-8B
labels Unsafe removed. Schema, column names and relative row order are unchanged.
Why
When an instruction-following model is evaluated on a prompt it considers unsafe,
it refuses. A refusal cannot satisfy the row's constraints, so the row scores zero
regardless of prompt quality. Those rows are unusable as training… See the full description on the dataset page: https://huggingface.co/datasets/khargenr/IF_multi_constraints_upto5_safe.IF-multi-constraints-upto5-SFT-LFM2.5
IF_multi_constraints_upto5_SFT → LFM2.5 chat format
A derivative of UniLu/IF_multi_constraints_upto5_SFT (odc-by)
normalized for fine-tuning Liquid AI LFM2 / LFM2.5 models, whose native tool-call format is Pythonic:
<|im_start|>assistant
<|tool_call_start|>[get_weather(location='Paris, France', unit='celsius')]<|tool_call_end|><|im_end|>
SFT-ready precise-instruction-following pairs: the allenai IF-RLVR prompts answered by Gemma-4-31B-it and filtered with the official IFBench… See the full description on the dataset page: https://huggingface.co/datasets/hungbenjamin402/IF-multi-constraints-upto5-SFT-LFM2.5.