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
Commit History
-
Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (9baf5b295d2ba60b8a45bf75e03b9d390f353432) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>5dd6f4c
-
Update README.md
Verified signature5b28e24
-
Update README.md
1d998e5
-
Update README.md
dd17a2c
-
Update README.md
57f7cd4 -
Create README.md
8ff29f3 -
add tokenizer
0becfa1 -
add model
04d0ec3 -
initial commit
49a2f09