Instructions to use Jellevdl/checkpoint-24453 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jellevdl/checkpoint-24453 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="Jellevdl/checkpoint-24453")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Jellevdl/checkpoint-24453") model = AutoModelForQuestionAnswering.from_pretrained("Jellevdl/checkpoint-24453", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Jellevdl/checkpoint-24453: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/Jellevdl/checkpoint-24453/resolve/main/tokenizer.json
- Command line
-
hf download hf://Jellevdl/checkpoint-24453/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Jellevdl/checkpoint-24453/resolve/main/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.