Text Classification
Transformers
PyTorch
Safetensors
Marathi
English
multilingual
bert
codemix
text-embeddings-inference
Instructions to use l3cube-pune/me-hate-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/me-hate-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="l3cube-pune/me-hate-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/me-hate-bert") model = AutoModelForSequenceClassification.from_pretrained("l3cube-pune/me-hate-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
c1a35d2
1
Parent(s): 49d0f26
Update README.md
Browse files
README.md
CHANGED
|
@@ -18,6 +18,8 @@ MeHate-BERT is a MeBERT-Mixed-v2 model fine-tuned on L3Cube-MeHate, a codemixed
|
|
| 18 |
<br>
|
| 19 |
[dataset link] (https://github.com/l3cube-pune/MarathiNLP)
|
| 20 |
|
|
|
|
|
|
|
| 21 |
More details on the dataset, models, and baseline results can be found in our [paper] (https://arxiv.org/abs/2306.14030)
|
| 22 |
|
| 23 |
Other models from the MeBERT family: <br>
|
|
|
|
| 18 |
<br>
|
| 19 |
[dataset link] (https://github.com/l3cube-pune/MarathiNLP)
|
| 20 |
|
| 21 |
+
LABEL_0 = Non-Hate, LABEL_1 = Hate
|
| 22 |
+
|
| 23 |
More details on the dataset, models, and baseline results can be found in our [paper] (https://arxiv.org/abs/2306.14030)
|
| 24 |
|
| 25 |
Other models from the MeBERT family: <br>
|