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Update README.md
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README.md
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@@ -62,7 +62,7 @@ We would like to take this opportunity to thank
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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model_id = "Local-Novel-LLM-project/Vecteus-
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new_tokens = 1024
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model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True, torch_dtype=torch.float16, attn_implementation="flash_attention_2", device_map="auto")
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print(tokenizer.batch_decode(generated_ids)[0])
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````
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- VT0.1 = Ninjav1 + Original Lora
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- VT0.2 = Ninjav1 128k + Original Lora
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- VT0.2on0.1 = VT0.1 + VT0.2
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- VT1 = all VT Series + Lora + Ninja 128k and Normal
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## Other points to keep in mind
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- The training data may be biased. Be careful with the generated sentences.
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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model_id = "Local-Novel-LLM-project/Vecteus-Poet"
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new_tokens = 1024
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model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True, torch_dtype=torch.float16, attn_implementation="flash_attention_2", device_map="auto")
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print(tokenizer.batch_decode(generated_ids)[0])
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````
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## Other points to keep in mind
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- The training data may be biased. Be careful with the generated sentences.
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