Instructions to use twmkn9/albert-base-v2-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use twmkn9/albert-base-v2-squad2 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="twmkn9/albert-base-v2-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("twmkn9/albert-base-v2-squad2") model = AutoModelForQuestionAnswering.from_pretrained("twmkn9/albert-base-v2-squad2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
TemporalMesh Transformer: 29.4 PPL at 48% compute — beats Mamba, new open-source architecture
#2 opened 5 months ago
by
vigneshwar234
Adding `safetensors` variant of this model
#1 opened over 3 years ago
by
SFconvertbot