Instructions to use csarron/roberta-large-squad-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use csarron/roberta-large-squad-v1 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="csarron/roberta-large-squad-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("csarron/roberta-large-squad-v1") model = AutoModelForQuestionAnswering.from_pretrained("csarron/roberta-large-squad-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from csarron/roberta-large-squad-v1: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/csarron/roberta-large-squad-v1/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://csarron/roberta-large-squad-v1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/csarron/roberta-large-squad-v1/resolve/main/flax_model.msgpack
1.42 GB
- Xet hash:
- 287211ec556d3bd3ff1bdf87c00f3dca3bd8cf64136015de2c4e89899f68e599
- Size of remote file:
- 1.42 GB
- SHA256:
- 49f4d0e9ac4eeee1e718558e83dddef2c01ee4e068d392d62f7853da2e96b269
路
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