datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SoMi-ToM
SoMi-ToM: Evaluating Multi-Perspective Theory of Mind in Embodied Social Interactions
NeurIPS 2025
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SoMi-ToM Benchmark
We propose the SoMi-ToM benchmark, designed to evaluate multi-perspective ToM in embodied multi-agent complex social interactions. This benchmark is based on rich multimodal interaction data generated by the interaction environment SoMi… See the full description on the dataset page: https://huggingface.co/datasets/hch2000/SoMi-ToM.code_instructions_120k_alpaca_filteredcodealpaka_20k_filteredtoefl_speakingqwen2.5-1.5b-blind-spots
Qwen2.5-1.5B Blind Spots Dataset
Model Tested
Model: Qwen/Qwen2.5-1.5B
Parameters: 1.5 Billion
Type: Base language model (not instruction-tuned)
Release date: Within the last 6 months
How I Loaded the Model
!pip install transformers accelerate -q
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_name = "Qwen/Qwen2.5-1.5B"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(… See the full description on the dataset page: https://huggingface.co/datasets/hchrAsma/qwen2.5-1.5b-blind-spots.