Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Cielciel/aift-model-review-multiple-label-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cielciel/aift-model-review-multiple-label-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cielciel/aift-model-review-multiple-label-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cielciel/aift-model-review-multiple-label-classification") model = AutoModelForSequenceClassification.from_pretrained("Cielciel/aift-model-review-multiple-label-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 492 Bytes
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from setuptools import find_packages
from setuptools import setup
import setuptools
from distutils.command.build import build as _build
import subprocess
REQUIRED_PACKAGES = [
'transformers',
'datasets',
'tqdm',
'cloudml-hypertune'
]
setup(
name='trainer',
version='0.1',
install_requires=REQUIRED_PACKAGES,
packages=find_packages(),
include_package_data=True,
description='Vertex AI | Training | PyTorch | Text Classification | Python Package'
)
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