Text Classification
Transformers
Safetensors
Bengali
English
xlm-roberta
safeage
safety-classification
bangla
banglish
text-embeddings-inference
Instructions to use mehedi4/SafeAge-XLM-R-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mehedi4/SafeAge-XLM-R-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mehedi4/SafeAge-XLM-R-Base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mehedi4/SafeAge-XLM-R-Base") model = AutoModelForSequenceClassification.from_pretrained("mehedi4/SafeAge-XLM-R-Base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download provenance/weight_update_check.json from mehedi4/SafeAge-XLM-R-Base: direct link, hf CLI and curl.
- Browser
- Download file 231 Bytes
-
https://huggingface.co/mehedi4/SafeAge-XLM-R-Base/resolve/main/provenance/weight_update_check.json
- Command line
-
hf download hf://mehedi4/SafeAge-XLM-R-Base/provenance/weight_update_check.json
-
curl -L -o weight_update_check.json https://huggingface.co/mehedi4/SafeAge-XLM-R-Base/resolve/main/provenance/weight_update_check.json
231 Bytes
| { | |
| "changed": true, | |
| "initial_classifier_head_sha256": "8525992b7c0f62ea5e7d4d9ba33a20aa71acf73016426ef8315c03aa6386e112", | |
| "selected_classifier_head_sha256": "79dc02c2255263b0d4b98924ab1a23831c33d92c4505deda2b88e3f6b5027f1d" | |
| } | |