Instructions to use ramkrish120595/debug_seq2seq_squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ramkrish120595/debug_seq2seq_squad 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="ramkrish120595/debug_seq2seq_squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ramkrish120595/debug_seq2seq_squad") model = AutoModelForQuestionAnswering.from_pretrained("ramkrish120595/debug_seq2seq_squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ramkrish120595/debug_seq2seq_squad: direct link, hf CLI and curl.
- Browser
- Download file 2.24 GB
-
https://huggingface.co/ramkrish120595/debug_seq2seq_squad/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ramkrish120595/debug_seq2seq_squad/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ramkrish120595/debug_seq2seq_squad/resolve/main/pytorch_model.bin
2.24 GB
- Xet hash:
- 142609f0bf32481dfd6c96112e33db5d29b7babed9e1a33203aba52e6942fe8b
- Size of remote file:
- 2.24 GB
- SHA256:
- ca287c0dbd09f9416f1f4c3575e7af2631b4fb01d9566599f19b35ab23e2f5ac
路
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