Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use abigailp/m1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abigailp/m1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abigailp/m1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abigailp/m1") model = AutoModelForSequenceClassification.from_pretrained("abigailp/m1") - Notebooks
- Google Colab
- Kaggle
Gated model You can list files but not access them
Preview of files found in this repository
- Apr10_19-46-48_cdf251d58037
- Apr10_19-51-26_cdf251d58037
- Apr10_20-01-23_cdf251d58037
- Dec18_14-05-01_9fb3cd086882
- Dec20_17-22-25_23a62778e773
- Dec20_17-48-45_23a62778e773
- Dec20_18-33-40_23a62778e773
- Dec20_18-57-58_23a62778e773
- Dec21_04-16-43_a89ec64e9864
- Dec21_09-09-16_e12d0bab50a2
- Dec21_09-26-04_e12d0bab50a2
- Dec21_09-47-44_e12d0bab50a2
- Dec21_10-13-31_e12d0bab50a2
- Dec23_14-57-49_d9182de706c0
- Dec23_15-09-24_d9182de706c0
- Dec23_15-21-46_d9182de706c0
- Dec23_15-27-27_d9182de706c0
- Dec23_15-37-09_d9182de706c0
- Dec23_15-41-38_d9182de706c0
- Dec23_16-43-09_d9182de706c0
- Dec23_16-50-04_d9182de706c0
- Dec23_16-56-59_d9182de706c0
- Dec23_17-03-48_d9182de706c0
- Dec23_17-27-30_d9182de706c0
- Dec24_05-08-31_a157876d5fd6
- Dec24_05-35-18_a157876d5fd6