Text Classification
Transformers
PyTorch
JAX
Safetensors
English
distilbert
text-embeddings-inference
Instructions to use hidude562/Wiki-Complexity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hidude562/Wiki-Complexity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hidude562/Wiki-Complexity")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hidude562/Wiki-Complexity") model = AutoModelForSequenceClassification.from_pretrained("hidude562/Wiki-Complexity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -2,7 +2,7 @@
|
|
| 2 |
tags: autotrain
|
| 3 |
language: en
|
| 4 |
widget:
|
| 5 |
-
- text: "I
|
| 6 |
datasets:
|
| 7 |
- hidude562/autotrain-data-SimpleDetect
|
| 8 |
co2_eq_emissions: 0.21691606119445225
|
|
|
|
| 2 |
tags: autotrain
|
| 3 |
language: en
|
| 4 |
widget:
|
| 5 |
+
- text: "I quite enjoy using AutoTrain due to its simplicity"
|
| 6 |
datasets:
|
| 7 |
- hidude562/autotrain-data-SimpleDetect
|
| 8 |
co2_eq_emissions: 0.21691606119445225
|