Instructions to use Sindhu/muril-large-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sindhu/muril-large-squad2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="Sindhu/muril-large-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Sindhu/muril-large-squad2") model = AutoModelForQuestionAnswering.from_pretrained("Sindhu/muril-large-squad2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Sindhu/muril-large-squad2: direct link, hf CLI and curl.
- Browser
- Download file 4.83 MB
-
https://huggingface.co/Sindhu/muril-large-squad2/resolve/main/tokenizer.json
- Command line
-
hf download hf://Sindhu/muril-large-squad2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Sindhu/muril-large-squad2/resolve/main/tokenizer.json
4.83 MB
File too large to display, you can check the raw version instead.