Text Classification
Transformers
English
bert
minbert
transformer
sentiment
tokenizer
classification
Instructions to use GlowCheese/minBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GlowCheese/minBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GlowCheese/minBERT")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GlowCheese/minBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| import csv | |
| import math | |
| import torch | |
| import random | |
| import numpy as np | |
| import pandas as pd | |
| import torch.nn.functional as F | |
| from tqdm import tqdm | |
| from torch import nn, Tensor | |
| from types import SimpleNamespace | |
| from scipy.stats import spearmanr | |
| from torch.utils.data import Dataset, DataLoader | |
| from sklearn.metrics import f1_score, accuracy_score | |
| from utils import * | |
| from constants import * | |
| import random, numpy as np, argparse | |
| from types import SimpleNamespace | |
| import csv | |