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/environment.json from mehedi4/SafeAge-XLM-R-Base: direct link, hf CLI and curl.
- Browser
- Download file 515 Bytes
-
https://huggingface.co/mehedi4/SafeAge-XLM-R-Base/resolve/main/provenance/environment.json
- Command line
-
hf download hf://mehedi4/SafeAge-XLM-R-Base/provenance/environment.json
-
curl -L -o environment.json https://huggingface.co/mehedi4/SafeAge-XLM-R-Base/resolve/main/provenance/environment.json
515 Bytes
| { | |
| "versions": { | |
| "torch": "2.11.0+cu128", | |
| "transformers": "5.5.4", | |
| "accelerate": "1.13.0", | |
| "numpy": "2.1.3", | |
| "pandas": "2.3.3", | |
| "scikit-learn": "1.6.1", | |
| "tokenizers": "0.22.2", | |
| "huggingface-hub": "1.29.0" | |
| }, | |
| "cuda_version": "12.8", | |
| "world_size": 2, | |
| "effective_batch_size": 32, | |
| "model_revision": "e73636d4f797dec63c3081bb6ed5c7b0bb3f2089", | |
| "model_path": "/kaggle/working/hf_cache/models--FacebookAI--xlm-roberta-base/snapshots/e73636d4f797dec63c3081bb6ed5c7b0bb3f2089" | |
| } | |