Instructions to use InfAI/flan-t5-text2sparql-custom-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InfAI/flan-t5-text2sparql-custom-tokenizer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("InfAI/flan-t5-text2sparql-custom-tokenizer") model = AutoModelForSeq2SeqLM.from_pretrained("InfAI/flan-t5-text2sparql-custom-tokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from InfAI/flan-t5-text2sparql-custom-tokenizer: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/InfAI/flan-t5-text2sparql-custom-tokenizer/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://InfAI/flan-t5-text2sparql-custom-tokenizer/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/InfAI/flan-t5-text2sparql-custom-tokenizer/resolve/main/pytorch_model.bin
990 MB
- Xet hash:
- 840cb38a57d7d4215ef6b2862b34967d4bee8b653ca77749009ea76bee0f2874
- Size of remote file:
- 990 MB
- SHA256:
- 610f1654fee96a3e5a4fbd6989f6365dbb791b09895bc65d1deba23839faa4c3
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