Text Classification
Transformers
Safetensors
modernbert
git
github
issue
difficulty
text-embeddings-inference
Instructions to use FOSSistant/FOSSistant-Difficulty-Prediction-v0.3.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FOSSistant/FOSSistant-Difficulty-Prediction-v0.3.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FOSSistant/FOSSistant-Difficulty-Prediction-v0.3.0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FOSSistant/FOSSistant-Difficulty-Prediction-v0.3.0") model = AutoModelForSequenceClassification.from_pretrained("FOSSistant/FOSSistant-Difficulty-Prediction-v0.3.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
library_name: transformers
tags:
- git
- github
- issue
- difficulty
datasets:
- FOSSistant/github-issues-v0.3.0
base_model:
- answerdotai/ModernBERT-large
pipeline_tag: text-classification
FOSSistant-Difficulty-Prediction-v0.3.0
Model Details
Model Description
- Developed by: Unchun Yang
- Finetuned from model: answerdotai/ModernBERT-large
Model Sources
- Repository: GitHub
Bias, Risks, and Limitations
Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model.