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daway845/huihui1.4.10_public

published by @daway845

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
1.1K
Last 30 days
38
Likes
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Size
10.1 GB
Created on HF
2026-03-20
Age
7 months ago

Description

huihui1.4.10_A40

This model is a fine-tuned version of daway845/Qwen2.5-32B-Coder-Abliterated-4bit on the huihui1.4 dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05… See the full description on the dataset page: https://huggingface.co/datasets/daway845/huihui1.4.10_public.

Tags

license:otherregion:usbase_model:adapter:daway845/Qwen2.5-32B-Coder-Abliterated-4bitllama-factoryloratransformers

README current version from Hugging Face

library_name: peft
license: other
base_model: daway845/Qwen2.5-32B-Coder-Abliterated-4bit
tags:

  • base_model:adapter:daway845/Qwen2.5-32B-Coder-Abliterated-4bit
  • llama-factory
  • lora
  • transformers
    pipeline_tag: text-generation
    model-index:
  • name: huihui1.4.10_A40
    results: []

huihui1.4.10_A40

This model is a fine-tuned version of daway845/Qwen2.5-32B-Coder-Abliterated-4bit on the huihui1.4 dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 0.1
  • num_epochs: 1.8
  • mixed_precision_training: Native AMP

Training results

Framework versions

  • PEFT 0.18.1
  • Transformers 5.2.0
  • Pytorch 2.5.1+cu121
  • Datasets 4.0.0
  • Tokenizers 0.22.2

README history 2 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

  1. 2026-03-20🎉 32B LoRA 2.0 Epochs 進攻版成果：全自動搬遷完畢！7e4c3bc1.5 KB
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  2. 2026-03-20initial commit93527040 B
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Used by abliterated models none yet

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Read further

Community best practices (ablation)
5 rules from KL-optimisation to layer-0 preservation.
M1 - Direct removal
The canonical Arditi-style ablation.
M3 - Layer-wise ablation
Selective abliteration limited to a band of layers.
Non-English abliteration communities
The Chinese layer-window heuristic and huihui-ai practice.

Metadata

License
other

Repository

DIR checkpoint-100 12 files DIR checkpoint-108 12 files DIR checkpoint-20 12 files DIR checkpoint-40 12 files DIR checkpoint-60 12 files DIR checkpoint-80 12 files FILE .gitattributes FILE adapter_config.json FILE adapter_model.safetensors FILE all_results.json FILE chat_template.jinja FILE README.md FILE tokenizer_config.json FILE tokenizer.json FILE train_results.json FILE trainer_log.jsonl FILE trainer_state.json FILE training_args.bin

File contents live on Hugging Face. Click a file or folder to open it there.

Download the dataset

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Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python) 
from datasets import load_dataset
ds = load_dataset("daway845/huihui1.4.10_public")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="daway845/huihui1.4.10_public", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/daway845/huihui1.4.10_public
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