Instructions to use tals/albert-base-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tals/albert-base-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tals/albert-base-mnli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tals/albert-base-mnli") model = AutoModelForSequenceClassification.from_pretrained("tals/albert-base-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model (#2)
Verified signature- Adding `safetensors` variant of this model (a88914dc0ba7dab27deaafb09aa2ac25e2e08237) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>35e70cf
-
Update README.md
e92674c
-
Update README.md
8b229c5
-
Update README.md
9015fc8
-
Create README.md
cfe5e60
-
model files
TalSchuster9dd8060 -
initial commit
c92066d