| | --- |
| | pipeline_tag: text-generation |
| | inference: true |
| | widget: |
| | - text: 'Hello!' |
| | example_title: Hello world |
| | group: Python |
| | library_name: transformers |
| | --- |
| | |
| | This model is randomly initialized, using the config from [EleutherAI/gpt-j-6b](https://huggingface.co/EleutherAI/gpt-j-6b) but with smaller size. |
| | Note the model is in float16. |
| |
|
| | Codes: |
| | ```python |
| | from transformers import pipeline |
| | from huggingface_hub import create_repo, upload_folder |
| | import torch |
| | import transformers |
| | import os |
| | |
| | model_id = 'EleutherAI/gpt-j-6b' |
| | save_path = '/tmp/yujiepan/gptj-tiny-random' |
| | repo_id = 'yujiepan/gptj-tiny-random' |
| | |
| | config = transformers.AutoConfig.from_pretrained(model_id) |
| | config.hidden_size = 16 |
| | config.n_embd = 16 |
| | config.num_attention_heads = 2 |
| | config.n_head = 2 |
| | config.rotary_dim = 4 |
| | config.num_hidden_layers = 2 |
| | config.n_layer = 2 |
| | config.torch_dtype = torch.float16 |
| | print(config) |
| | |
| | model = transformers.AutoModelForCausalLM.from_config(config, torch_dtype=torch.float16) |
| | model = model.half() |
| | model.save_pretrained(save_path) |
| | |
| | tokenizer = transformers.AutoTokenizer.from_pretrained(model_id) |
| | tokenizer.save_pretrained(save_path) |
| | |
| | # from optimum.intel.openvino import OVModelForCausalLM |
| | # ovmodel = OVModelForCausalLM.from_pretrained(save_path, export=True) |
| | # ovmodel.save_pretrained(save_path) |
| | |
| | os.system(f'ls -alh {save_path}') |
| | create_repo(repo_id, exist_ok=True) |
| | upload_folder(repo_id=repo_id, folder_path=save_path) |
| | ``` |