Instructions to use Kaludi/eurekaQA-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kaludi/eurekaQA-model 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="Kaludi/eurekaQA-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Kaludi/eurekaQA-model") model = AutoModelForQuestionAnswering.from_pretrained("Kaludi/eurekaQA-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Kaludi/eurekaQA-model: direct link, hf CLI and curl.
- Browser
- Download file 669 kB
-
https://huggingface.co/Kaludi/eurekaQA-model/resolve/main/tokenizer.json
- Command line
-
hf download hf://Kaludi/eurekaQA-model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Kaludi/eurekaQA-model/resolve/main/tokenizer.json
669 kB
- Xet hash:
- 85295842c86959731f8f6cebcccda1fe7960188db5e1601e42f58d1a944d0410
- Size of remote file:
- 669 kB
- SHA256:
- e8b2d0bbdc816a0af026b240e62f27d2d98d104f418e980225c40b60ca18f204
路
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