---
pipeline_tag: text-generation
inference: true
widget:
- text: 'Hello!'
  example_title: Hello world
  group: Python
library_name: transformers
---

# yujiepan/opt-tiny-2layers-random

This model is **randomly initialized**, using the config from [https://huggingface.co/facebook/opt-30b] but the size is smaller.
Note the model is in float32.

```python
config.ffn_dim = 32
config.hidden_size = 8
config.num_attention_heads = 2
config.num_hidden_layers = 2
config.word_embed_proj_dim = 8
```

Codes for this model:
```python
import torch
import transformers
import os
from optimum.intel.openvino import OVModelForCausalLM

save_path = '/tmp/yujiepan/opt-tiny-2layers-random'
repo_id = 'yujiepan/opt-tiny-2layer-random'

config = transformers.AutoConfig.from_pretrained('facebook/opt-30b')
config.ffn_dim = 32
config.hidden_size = 8
config.num_attention_heads = 2
config.num_hidden_layers = 2
config.word_embed_proj_dim = 8

model = transformers.AutoModelForCausalLM.from_config(config, torch_dtype=torch.float32)
model.save_pretrained(save_path)

tokenizer = transformers.AutoTokenizer.from_pretrained('facebook/opt-30b')
tokenizer.save_pretrained(save_path)

ovmodel = OVModelForCausalLM.from_pretrained(save_path, export=True)
ovmodel.save_pretrained(save_path)

os.system(f'ls -alh {save_path}')

from huggingface_hub import create_repo, upload_folder
create_repo(repo_id, exist_ok=True)
upload_folder(repo_id=repo_id, folder_path=save_path)
```