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 tokenizer.json from ramkrish120595/debug_seq2seq_squad: direct link, hf CLI and curl.
- Browser
- Download file 14.5 MB
-
https://huggingface.co/ramkrish120595/debug_seq2seq_squad/resolve/main/tokenizer.json
- Command line
-
hf download hf://ramkrish120595/debug_seq2seq_squad/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ramkrish120595/debug_seq2seq_squad/resolve/main/tokenizer.json
14.5 MB
- Xet hash:
- 9a1c45dfad0c99c40ad183926a7c86b224adf20aa76782cc84e3b2ec92e33ff5
- Size of remote file:
- 14.5 MB
- SHA256:
- 524b175a100e5a52b0cc6590fc43c05092458363cc576ac7717c17efc2410af3
路
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