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@@ -83,7 +83,7 @@ The following examples was obtained with `temperature = 0.85`.
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  <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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- CelineGPT-12B-240831 was trained on a diverse, *French-only* corpus consisting of:
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  - All available interviews (TV, radio, written) given by Céline;
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  - A significant portion of Céline's correspondence, manually transformed into question-and-answer pairs;
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  - Portions of Céline's post-war works, notably the dialogues in 'Conversations with Professor Y,' 'Castle to Castle,' 'North,' 'Rigadoon,' 'Fable for Another Time,' and various other texts.
@@ -112,7 +112,7 @@ import torch
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  from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig, TextStreamer
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  # The HF repo of the model
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- model_id = "krogoldAI/CelineGPT-12B-240831"
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  # Use GPU when available
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  device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
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  <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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+ CelineGPT-12B-v0.1 was trained on a diverse, *French-only* corpus consisting of:
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  - All available interviews (TV, radio, written) given by Céline;
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  - A significant portion of Céline's correspondence, manually transformed into question-and-answer pairs;
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  - Portions of Céline's post-war works, notably the dialogues in 'Conversations with Professor Y,' 'Castle to Castle,' 'North,' 'Rigadoon,' 'Fable for Another Time,' and various other texts.
 
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  from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig, TextStreamer
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  # The HF repo of the model
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+ model_id = "krogoldAI/CelineGPT-12B-v0.1"
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  # Use GPU when available
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  device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")