Instructions to use mkly/crypto-sales with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mkly/crypto-sales with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "mkly/crypto-sales") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Training procedure
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language:
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# Adapter `mkly/crypto_sales` for `meta-llama/Llama-2-7b-chat-hf`
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An adapter for the [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) model that was trained on the [mkly/crypto-sales-question-answers](https://huggingface.co/datasets/mkly/crypto-sales-question-answers/) dataset.
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## Training procedure
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