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C-Lo/unfiltered-dataset

Name: C-Lo/unfiltered-dataset
Author: C-Lo

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classification unknown
files 10
author_summary 2 models
readme_text full

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Abliteration classifier · v1.0.0

Primary method

Unclassified

No clear signals of an abliteration technique in this model.

Confidence

UNKNOWN

Why this label 1 signal

No classification signals present. This may not be an abliterated model at all - it could be a repackaging, a merge with unrelated goals, or unrelated content that mentions the term.

no classification signals present (no abliterated, uncensored, or known producer/method markers)

Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

Downloads · 30-day

↑ 2,250% in 90 days

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Model age

3.2y ago

created 2023-08-08

Training datasets

Corpora the author lists in the model card. Datasets tracked in our /datasets catalog carry a category badge linking to the workflow stage. Others open on Hugging Face.

imdb

Downloads over time

Jul 24, 2024 → Oct 11 · 155 snapshots · spans 809 days

Metadata

License

apache-2.0

Files by quantization

Auxiliary files 10 files 256 MB

pytorch_model.bin	255 MB	ac278e7b	download
training_args.bin	3.50 KB	e64be581	download
tokenizer.json	695 KB	05a08d51	download
vocab.txt	226 KB	fb140275	download
.gitattributes	1.48 KB	a6344aac	download
README.md	1.04 KB	05368589	download
config.json	615 B	2e035ba1	download
tokenizer_config.json	320 B	4ef60ec0	download
special_tokens_map.json	125 B	a8b3208c	download
.gitignore	13.0 B	0348ea97	download

README current version from Hugging Face

license: apache-2.0
tags:

generated_from_trainer
datasets:
imdb
model-index:
name: unfiltered-dataset
results: []

unfiltered-dataset

This model is a fine-tuned version of distilbert-base-uncased on the imdb 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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6

Training results

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3

README history 1 version

The author's README evolved over time. Click a version to see its content at that point.

2023-08-08update model card README.mdfc6b21d1 KB
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Discussions 1 thread

2024-12-18PRAdding `safetensors` variant of this modelopen1 💬#1
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C-Lo/unfiltered-dataset

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Unclassified

Training datasets

Metadata

Related

Files by quantization

README current version from Hugging Face

unfiltered-dataset

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

README history 1 version

Discussions 1 thread

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