Instructions to use khailai/roberta-offensive-classifier-beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use khailai/roberta-offensive-classifier-beta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="khailai/roberta-offensive-classifier-beta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("khailai/roberta-offensive-classifier-beta") model = AutoModelForSequenceClassification.from_pretrained("khailai/roberta-offensive-classifier-beta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Trained on training set of DICA_Dec15 (lower-cased) for 5 epochs.
Browse files- config.json +1 -1
- tf_model.h5 +1 -1
config.json
CHANGED
|
@@ -40,7 +40,7 @@
|
|
| 40 |
"num_hidden_layers": 12,
|
| 41 |
"pad_token_id": 1,
|
| 42 |
"position_embedding_type": "absolute",
|
| 43 |
-
"transformers_version": "4.
|
| 44 |
"type_vocab_size": 1,
|
| 45 |
"use_cache": true,
|
| 46 |
"vocab_size": 50265
|
|
|
|
| 40 |
"num_hidden_layers": 12,
|
| 41 |
"pad_token_id": 1,
|
| 42 |
"position_embedding_type": "absolute",
|
| 43 |
+
"transformers_version": "4.12.5",
|
| 44 |
"type_vocab_size": 1,
|
| 45 |
"use_cache": true,
|
| 46 |
"vocab_size": 50265
|
tf_model.h5
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 498896768
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:56f28b481b5516906aff5e2a9c187e658b01ef453353a97c4c71f9c2920ef398
|
| 3 |
size 498896768
|