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README.md
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@@ -41,12 +41,12 @@ torch.set_default_device('cpu') # or 'cuda'
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# create model
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model = AutoModelForCausalLM.from_pretrained(
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'BAAI/
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torch_dtype=torch.float16,
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device_map='auto',
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trust_remote_code=True)
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tokenizer = AutoTokenizer.from_pretrained(
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'BAAI/
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trust_remote_code=True)
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# text prompt
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@@ -55,7 +55,7 @@ text = f"A chat between a curious user and an artificial intelligence assistant.
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text_chunks = [tokenizer(chunk).input_ids for chunk in text.split('<image>')]
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input_ids = torch.tensor(text_chunks[0] + [-200] + text_chunks[1], dtype=torch.long).unsqueeze(0)
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# image, sample images can be found in
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image = Image.open('example_2.png')
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image_tensor = model.process_images([image], model.config).to(dtype=model.dtype)
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@@ -72,7 +72,7 @@ print(tokenizer.decode(output_ids[input_ids.shape[1]:], skip_special_tokens=True
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Before running the snippet, you need to install the following dependencies:
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```shell
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pip install torch transformers accelerate
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```
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# License
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# create model
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model = AutoModelForCausalLM.from_pretrained(
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'BAAI/Bunny-v1_0-3B',
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torch_dtype=torch.float16,
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device_map='auto',
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trust_remote_code=True)
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tokenizer = AutoTokenizer.from_pretrained(
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'BAAI/Bunny-v1_0-3B',
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trust_remote_code=True)
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# text prompt
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text_chunks = [tokenizer(chunk).input_ids for chunk in text.split('<image>')]
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input_ids = torch.tensor(text_chunks[0] + [-200] + text_chunks[1], dtype=torch.long).unsqueeze(0)
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# image, sample images can be found in images folder
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image = Image.open('example_2.png')
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image_tensor = model.process_images([image], model.config).to(dtype=model.dtype)
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Before running the snippet, you need to install the following dependencies:
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```shell
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pip install torch transformers accelerate pillow
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```
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# License
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