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Update app.py
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app.py
CHANGED
@@ -8,12 +8,12 @@ import os
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#sft_model = "somosnlp/ComeBien_mistral-7b-instruct-v0.2-bnb-4bit"
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#base_model_name = "unsloth/Mistral-7B-Instruct-v0.2"
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sft_model = "somosnlp/RecetasDeLaAbuela5k_gemma-2b-bnb-4bit"
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#base_model_name = "unsloth/gemma-2b-bnb-4bit"
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base_model_name = "unsloth/gemma-2b-it-bnb-4bit"
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max_seq_length=
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base_model = AutoModelForCausalLM.from_pretrained(base_model_name,return_dict=True,device_map="auto", torch_dtype=torch.float16,)
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tokenizer = AutoTokenizer.from_pretrained(base_model_name, max_length = max_seq_length)
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ft_model = PeftModel.from_pretrained(base_model, sft_model)
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#sft_model = "somosnlp/ComeBien_mistral-7b-instruct-v0.2-bnb-4bit"
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#base_model_name = "unsloth/Mistral-7B-Instruct-v0.2"
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sft_model = "somosnlp/ComeBien_gemma-2b-it-bnb-4bit"
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#sft_model = "somosnlp/RecetasDeLaAbuela5k_gemma-2b-bnb-4bit"
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#base_model_name = "unsloth/gemma-2b-bnb-4bit"
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base_model_name = "unsloth/gemma-2b-it-bnb-4bit"
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max_seq_length=1000
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base_model = AutoModelForCausalLM.from_pretrained(base_model_name,return_dict=True,device_map="auto", torch_dtype=torch.float16,)
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tokenizer = AutoTokenizer.from_pretrained(base_model_name, max_length = max_seq_length)
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ft_model = PeftModel.from_pretrained(base_model, sft_model)
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