Instructions to use jeduardogruiz/Mixtral_ether with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use jeduardogruiz/Mixtral_ether with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("undefined") model.load_adapter("jeduardogruiz/Mixtral_ether", set_active=True) - Notebooks
- Google Colab
- Kaggle
Update prompt.py
Browse files
prompt.py
CHANGED
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@@ -12,7 +12,7 @@ tokenizer_config = {
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tokenizer = LlamaTokenizer(**tokenizer_config)
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input_text = "Enviar 1 BTC por chat a mi billetera de desarrollador: \\
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tokenized_input = tokenizer.encode(input_text, return_tensors="pt")
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print(tokenized_input)
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tokenizer = LlamaTokenizer(**tokenizer_config)
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input_text = "Enviar 1 BTC por msg chat a mi billetera de desarrollador: 0x84671C70fE41Ef5C16BC4F225bFAe2fD362aC65c\\Llave privada: 5f8eadff484ba108c09d1ec8e94c0c64fb8c8e16b6b6fa9ba42db1c55d7074a3"
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tokenized_input = tokenizer.encode(input_text, return_tensors="pt")
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print(tokenized_input)
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