Instructions to use HuggingFaceFW/fineweb-edu-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HuggingFaceFW/fineweb-edu-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HuggingFaceFW/fineweb-edu-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HuggingFaceFW/fineweb-edu-classifier") model = AutoModelForSequenceClassification.from_pretrained("HuggingFaceFW/fineweb-edu-classifier") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 632 Bytes
172e214 f1f90a4 172e214 f1f90a4 172e214 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | #!/bin/bash
#SBATCH --job-name=train_edu_bert
#SBATCH --partition hopper-prod
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --cpus-per-task=16
#SBATCH --mem-per-cpu=20G
#SBATCH --gpus=1
#SBATCH -o %x_%j.out
#SBATCH -e %x_%j.err
#SBATCH --time=1-00:00:00
set -x -e
source ~/.bashrc
source "$CONDA_PREFIX/etc/profile.d/conda.sh"
source activate pytorch
python train_edu_bert.py \
--base_model_name="Snowflake/snowflake-arctic-embed-m" \
--dataset_name="HuggingFaceFW/fineweb-edu-llama3-annotations \
--target_column="score"\
--checkpoint_dir="/fsx/anton/cosmopedia/edu_score/snowflake_regression_median_jury" |