Instructions to use xihajun/20_bert_base_pruned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xihajun/20_bert_base_pruned with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="xihajun/20_bert_base_pruned")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("xihajun/20_bert_base_pruned") model = AutoModelForQuestionAnswering.from_pretrained("xihajun/20_bert_base_pruned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened almost 2 years ago
by
SFconvertbot