Instructions to use Swarnadeep-28/bengali-code-mix-sentiment-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Swarnadeep-28/bengali-code-mix-sentiment-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("xlm-roberta-base") model = PeftModel.from_pretrained(base_model, "Swarnadeep-28/bengali-code-mix-sentiment-lora") - Transformers
How to use Swarnadeep-28/bengali-code-mix-sentiment-lora with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Swarnadeep-28/bengali-code-mix-sentiment-lora")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Swarnadeep-28/bengali-code-mix-sentiment-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Swarnadeep-28/bengali-code-mix-sentiment-lora: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/Swarnadeep-28/bengali-code-mix-sentiment-lora/resolve/main/tokenizer.json
- Command line
-
hf download hf://Swarnadeep-28/bengali-code-mix-sentiment-lora/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Swarnadeep-28/bengali-code-mix-sentiment-lora/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- c5ec463144c6e0060bcb4e9e73fd47716918a43c46696ad59fcbd9c580964153
- Size of remote file:
- 17.1 MB
- SHA256:
- 3c088c06cf975b7097e469bd69630cdb0d675c6db1ce3af1042b6e19c6d01f22
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