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README.md
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## Use in Transformers
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## Load model directly
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM, MistralForCausalLM
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model = MistralForCausalLM.from_pretrained("ai-agi/neural-zephyr", use_cache=False, torch_dtype=torch.bfloat16, device_map="auto") \
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state_dict = torch.load('model_weights.pth') \
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model.load_state_dict(state_dict)
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tokenizer = AutoTokenizer.from_pretrained("ai-agi/neural-zephyr", use_fast=True)
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tokenizer.pad_token = tokenizer.eos_token)
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## Use in Transformers
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## Load model directly
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import torch \
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from transformers import AutoTokenizer, AutoModelForCausalLM, MistralForCausalLM
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model = MistralForCausalLM.from_pretrained("ai-agi/neural-zephyr", use_cache=False, torch_dtype=torch.bfloat16, device_map="auto") \
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state_dict = torch.load('model_weights.pth') \
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model.load_state_dict(state_dict)
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tokenizer = AutoTokenizer.from_pretrained("ai-agi/neural-zephyr", use_fast=True) \
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if tokenizer.pad_token is None: \
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tokenizer.pad_token = tokenizer.eos_token)
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