Instructions to use VinsmokeMir/Method_1_FineTuneONSC_OurModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VinsmokeMir/Method_1_FineTuneONSC_OurModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VinsmokeMir/Method_1_FineTuneONSC_OurModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VinsmokeMir/Method_1_FineTuneONSC_OurModel") model = AutoModelForSequenceClassification.from_pretrained("VinsmokeMir/Method_1_FineTuneONSC_OurModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from VinsmokeMir/Method_1_FineTuneONSC_OurModel: direct link, hf CLI and curl.
- Browser
- Download file 48 Bytes
-
https://huggingface.co/VinsmokeMir/Method_1_FineTuneONSC_OurModel/resolve/main/README.md
- Command line
-
hf download hf://VinsmokeMir/Method_1_FineTuneONSC_OurModel/README.md
-
curl -L -o README.md https://huggingface.co/VinsmokeMir/Method_1_FineTuneONSC_OurModel/resolve/main/README.md
48 Bytes
metadata
language:
- bn
metrics:
- accuracy
- f1