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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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This model is for debugging. It is randomly initialized using the config from [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) but with smaller size. |
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Codes: |
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```python |
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from transformers import pipeline |
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from huggingface_hub import create_repo, upload_folder |
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import torch |
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import transformers |
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import os |
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model_id = 'mistralai/Mistral-7B-Instruct-v0.3' |
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save_path = '/tmp/yujiepan/mistral-v0.3-tiny-random' |
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repo_id = 'yujiepan/mistral-v0.3-tiny-random' |
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config = transformers.AutoConfig.from_pretrained(model_id) |
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config.hidden_size = 8 |
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config.intermediate_size = 32 |
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config.num_attention_heads = 4 |
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config.num_hidden_layers = 2 |
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config.num_key_value_heads = 2 |
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config.head_dim = 2 |
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print(config) |
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tokenizer = transformers.AutoTokenizer.from_pretrained(model_id) |
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tokenizer.save_pretrained(save_path) |
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model = transformers.AutoModelForCausalLM.from_config(config, torch_dtype=torch.bfloat16) |
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model.generation_config = transformers.GenerationConfig.from_pretrained(model_id) |
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transformers.set_seed(42) |
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with torch.no_grad(): |
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for _, p in sorted(model.named_parameters()): |
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torch.nn.init.uniform_(p, -0.1, 0.1) |
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pipe = pipeline('text-generation', model=model, tokenizer=tokenizer, do_sample=False, device='cuda') |
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print(pipe('Hello World!')) |
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model.save_pretrained(save_path) |
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``` |
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