Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use ProceduralTree/final-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProceduralTree/final-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ProceduralTree/final-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ProceduralTree/final-model") model = AutoModelForSequenceClassification.from_pretrained("ProceduralTree/final-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
fdf7e70 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:b40224e06fd59adfb845b5374957acf448e042c7b850a981407bd720833c617c
size 438010997
|