Question Answering
Transformers
PyTorch
Safetensors
English
llama
text-generation
logical reasoning
reasoning
text-generation-inference
Instructions to use jzfeng/LoGiPT-CodeLlama-13b-hf-prontoqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jzfeng/LoGiPT-CodeLlama-13b-hf-prontoqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="jzfeng/LoGiPT-CodeLlama-13b-hf-prontoqa")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("jzfeng/LoGiPT-CodeLlama-13b-hf-prontoqa") model = AutoModelForCausalLM.from_pretrained("jzfeng/LoGiPT-CodeLlama-13b-hf-prontoqa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f18a3e31af371f514644a07ef51454912e704f2ed7957d0ef5e47bed71aa5f51
- Size of remote file:
- 500 kB
- SHA256:
- 45ccb9c8b6b561889acea59191d66986d314e7cbd6a78abc6e49b139ca91c1e6
路
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