Flan-ul2 Download [REPACK]

The flan-ul2-20b model is provided by Google on Hugging Face. This model was trained by using the Unifying Language Learning Paradigms (UL2). The model is optimized for language generation, language understanding, text classification, question answering, common sense reasoning, long text reasoning, structured-knowledge grounding, and information retrieval, in-context learning, zero-shot prompting, and one-shot prompting.

Instruction tuning information : The flan-ul2-20b model is pretrained on the colossal, cleaned version of Common Crawl's web crawl corpus. The model is fine-tuned with multiple pretraining objectives to optimize it for various natural language processing tasks. Details about the training data sets used are published.

Flan-ul2 Download

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Welcome to this Amazon SageMaker guide on how to deploy the FLAN-UL2 20B on Amazon SageMaker for inference. We will deploy google/flan-ul2 to Amazon SageMaker for real-time inference using Hugging Face Inference Deep Learning Container.

To use our inference.py we need to bundle it together with our model weights into a model.tar.gz. The archive includes all our model-artifcats to run inference. The inference.py script will be placed into a code/ folder. We will use the huggingface_hub SDK to easily downloadgoogle/flan-ul2 from Hugging Face and then upload it to Amazon S3 with the sagemaker SDK.

Background:

I want to try the LLM model, for example, flan-ul2 onto the two VM A10 GPUs provided by AWS, Each VM has 4 GPUs, so in my ray cluster I would have in total of 8 GPUs. Now, I want to create a ray cluster, which I already did by running the following commands: 2351a5e196