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🔧🐢 Lazy Transformer Patch ⚡️✨ (#2)
Browse files- 🔧🐢 Lazy Transformer Patch ⚡️✨ (e11a1c01a7e673f9928b03ed640fd0d3de9ca6a9)
Co-authored-by: AI-B <[email protected]>
app.py
CHANGED
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@@ -2,6 +2,11 @@ import gradio as gr
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, AutoConfig
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# Singleton for model and tokenizer
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_model = None
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_tokenizer = None
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@@ -10,19 +15,13 @@ def load_model():
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global _model, _tokenizer
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if _model is None or _tokenizer is None:
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model_id = "microsoft/bitnet-b1.58-2B-4T"
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config = AutoConfig.from_pretrained(
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model_id,
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trust_remote_code=True
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)
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_model = AutoModelForCausalLM.from_pretrained(
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model_id,
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config=config,
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torch_dtype=torch.bfloat16
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trust_remote_code=True
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)
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return _model, _tokenizer
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, AutoConfig
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# use the official bitnet package to supply the missing code
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from bitnet.configuration_bitnet import BitNetConfig
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from bitnet.modeling_bitnet import BitNetForCausalLM
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from bitnet.tokenization_bitnet import BitNetTokenizer
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# Singleton for model and tokenizer
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_model = None
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_tokenizer = None
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global _model, _tokenizer
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if _model is None or _tokenizer is None:
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model_id = "microsoft/bitnet-b1.58-2B-4T"
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# load tokenizer, config, and model from the bitnet pip package
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_tokenizer = BitNetTokenizer.from_pretrained(model_id)
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config = BitNetConfig.from_pretrained(model_id)
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_model = BitNetForCausalLM.from_pretrained(
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model_id,
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config=config,
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torch_dtype=torch.bfloat16
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)
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return _model, _tokenizer
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