Text Classification
Transformers
ONNX
Safetensors
fela-moderation
fela
fourier-neural-operator
fno
gated-linear-attention
cpu
on-device
content-moderation
toxicity
pii
byte-level
custom_code
Instructions to use lowdown-labs/fela-moderator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lowdown-labs/fela-moderator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lowdown-labs/fela-moderator", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("lowdown-labs/fela-moderator", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,222 Bytes
4751195 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | from transformers import PretrainedConfig
class FelaModeratorConfig(PretrainedConfig):
model_type = "fela-moderation"
def __init__(
self,
vocab_size=259,
max_len=512,
d_model=448,
n_layers=8,
n_heads=7,
fno_modes=128,
gla_chunk=32,
ffn_hidden=1280,
layer_pattern="SSSL",
dropout=0.1,
pad_id=256,
n_tox_labels=6,
n_pii_tags=113,
n_tax=19,
n_spam=3,
n_jailbreak=4,
n_nsfw=2,
n_identity=7,
**kwargs,
):
self.vocab_size = vocab_size
self.max_len = max_len
self.d_model = d_model
self.n_layers = n_layers
self.n_heads = n_heads
self.fno_modes = fno_modes
self.gla_chunk = gla_chunk
self.ffn_hidden = ffn_hidden
self.layer_pattern = layer_pattern
self.dropout = dropout
self.pad_id = pad_id
self.n_tox_labels = n_tox_labels
self.n_pii_tags = n_pii_tags
self.n_tax = n_tax
self.n_spam = n_spam
self.n_jailbreak = n_jailbreak
self.n_nsfw = n_nsfw
self.n_identity = n_identity
super().__init__(**kwargs)
|