yujiepan commited on
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1 Parent(s): e36c1c9

Upload folder using huggingface_hub

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ pipeline_tag: text-generation
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+ inference: true
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+ widget:
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+ - text: Hello!
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+ example_title: Hello world
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+ group: Python
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+ ---
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+
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+ This model is for debugging. It is randomly initialized using the config from [Qwen/Qwen2.5-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct) but with smaller size.
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+
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+ Codes:
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+ ```python
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+ import transformers
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+ import torch
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+ import os
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+ from huggingface_hub import create_repo, upload_folder
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+ import accelerate
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+
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+ model_id = 'Qwen/Qwen2.5-72B-Instruct'
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+ save_path = '/tmp/yujiepan/qwen2.5-tiny-random'
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+ repo_id = 'yujiepan/qwen2.5-tiny-random'
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+
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+ os.system(f'rm -rf {save_path}')
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+
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+ config = transformers.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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+ config._name_or_path = model_id
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+ config.hidden_size = 8
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+ config.intermediate_size = 16
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+ config.num_key_value_heads = 2
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+ config.num_attention_heads = 4
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+ config.num_hidden_layers = 2
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+ config.max_window_layers = 1
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+
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+ model = transformers.AutoModelForCausalLM.from_config(
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+ config,
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+ trust_remote_code=True,
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+ )
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+ model.generation_config = transformers.GenerationConfig.from_pretrained(
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+ model_id)
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+ model = model.to(torch.bfloat16)
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+
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+ with torch.no_grad():
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+ for p in model.parameters():
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+ torch.nn.init.normal_(p)
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+
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+ model.save_pretrained(save_path)
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+
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+ tokenizer = transformers.AutoTokenizer.from_pretrained(
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+ model_id,
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+ trust_remote_code=True,
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+ )
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+ tokenizer.save_pretrained(save_path)
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+
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+ output = model.float().generate(torch.tensor(
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+ [[1, 2, 3]]).long(), max_length=16, do_sample=True)
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+
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+ os.system(f'ls -alh {save_path}')
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+ # os.system(f'rm -rf {save_path}/model.safetensors')
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+ # create_repo(repo_id, exist_ok=True)
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+ # upload_folder(repo_id=repo_id, folder_path=save_path)
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+ ```
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