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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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# yujiepan/opt-tiny-2layers-random |
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This model is **randomly initialized**, using the config from [https://huggingface.co/facebook/opt-30b] but the size is smaller. |
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Note the model is in float32. |
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```python |
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config.ffn_dim = 32 |
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config.hidden_size = 8 |
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config.num_attention_heads = 2 |
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config.num_hidden_layers = 2 |
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config.word_embed_proj_dim = 8 |
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``` |
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Codes for this model: |
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```python |
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import torch |
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import transformers |
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import os |
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from optimum.intel.openvino import OVModelForCausalLM |
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save_path = '/tmp/yujiepan/opt-tiny-2layers-random' |
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repo_id = 'yujiepan/opt-tiny-2layer-random' |
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config = transformers.AutoConfig.from_pretrained('facebook/opt-30b') |
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config.ffn_dim = 32 |
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config.hidden_size = 8 |
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config.num_attention_heads = 2 |
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config.num_hidden_layers = 2 |
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config.word_embed_proj_dim = 8 |
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model = transformers.AutoModelForCausalLM.from_config(config, torch_dtype=torch.float32) |
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model.save_pretrained(save_path) |
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tokenizer = transformers.AutoTokenizer.from_pretrained('facebook/opt-30b') |
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tokenizer.save_pretrained(save_path) |
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ovmodel = OVModelForCausalLM.from_pretrained(save_path, export=True) |
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ovmodel.save_pretrained(save_path) |
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os.system(f'ls -alh {save_path}') |
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from huggingface_hub import create_repo, upload_folder |
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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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``` |
