Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use coderSounak/finetuning-insult-model-bert-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use coderSounak/finetuning-insult-model-bert-multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="coderSounak/finetuning-insult-model-bert-multilingual")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("coderSounak/finetuning-insult-model-bert-multilingual") model = AutoModelForSequenceClassification.from_pretrained("coderSounak/finetuning-insult-model-bert-multilingual") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#2
by librarian-bot - opened
README.md
CHANGED
|
@@ -7,6 +7,7 @@ metrics:
|
|
| 7 |
- f1
|
| 8 |
- precision
|
| 9 |
- recall
|
|
|
|
| 10 |
model-index:
|
| 11 |
- name: finetuning-insult-model-bert-multilingual
|
| 12 |
results: []
|
|
|
|
| 7 |
- f1
|
| 8 |
- precision
|
| 9 |
- recall
|
| 10 |
+
base_model: QCRI/bert-base-multilingual-cased-pos-english
|
| 11 |
model-index:
|
| 12 |
- name: finetuning-insult-model-bert-multilingual
|
| 13 |
results: []
|