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--- |
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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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library_name: transformers |
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--- |
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This model is randomly initialized, using the config from [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) but with smaller size. |
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Note the model is in float16. |
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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/Mixtral-8x7B-Instruct-v0.1' |
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save_path = '/tmp/yujiepan/mixtral-tiny-random' |
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repo_id = 'yujiepan/mixtral-tiny-random' |
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config = transformers.AutoConfig.from_pretrained(model_id) |
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config.hidden_size = 4 |
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config.intermediate_size = 8 |
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config.num_attention_heads = 4 |
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config.num_experts_per_tok = 2 |
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config.num_hidden_layers = 2 |
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config.num_key_value_heads = 2 |
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config.num_local_experts = 8 |
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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.float16) |
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model = model.half() |
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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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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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``` |