Create README.md
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README.md
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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 [ai21labs/Jamba-v0.1](https://huggingface.co/ai21labs/Jamba-v0.1/blob/main/config.json) 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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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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source_model_id = 'ai21labs/Jamba-v0.1'
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save_path = '/tmp/yujiepan/jamba-tiny-random'
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repo_id = 'yujiepan/jamba-tiny-random'
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config = transformers.AutoConfig.from_pretrained(
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source_model_id, trust_remote_code=True)
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config.hidden_size = 4
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config.intermediate_size = 6
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config.num_attention_heads = 4
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config.num_hidden_layers = 16
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config.num_key_value_heads = 2
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config.use_mamba_kernels = False
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model = transformers.AutoModelForCausalLM.from_config(
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config, trust_remote_code=True)
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model = model.half()
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model.save_pretrained(save_path)
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tokenizer = transformers.AutoTokenizer.from_pretrained(
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source_model_id, trust_remote_code=True)
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tokenizer.save_pretrained(save_path)
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result = transformers.pipelines.pipeline(
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'text-generation',
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model=model.float(), tokenizer=tokenizer)('Hello World!')
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print(result)
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os.system(f'ls -alh {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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```
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