Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use transformersbook/distilbert-base-uncased-distilled-clinc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use transformersbook/distilbert-base-uncased-distilled-clinc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="transformersbook/distilbert-base-uncased-distilled-clinc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("transformersbook/distilbert-base-uncased-distilled-clinc") model = AutoModelForSequenceClassification.from_pretrained("transformersbook/distilbert-base-uncased-distilled-clinc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| timestamp,experiment_id,project_name,duration,emissions,energy_consumed,country_name,country_iso_code,region,on_cloud,cloud_provider,cloud_region | |
| 2021-10-23T22:05:02,144ad1d7-1e4b-4372-b927-c9c9f5169029,codecarbon,256.7832429409027,0.010270217894205224,0.024188899267159385,France,FRA,île-de-france,N,, | |
| 2021-10-24T12:31:06,197d3925-b542-476f-a971-7dd66a898072,codecarbon,253.8993947505951,0.010109645646836344,0.023810711972915247,France,FRA,île-de-france,N,, | |