|
--- |
|
library_name: transformers |
|
pipeline_tag: text-generation |
|
inference: true |
|
widget: |
|
- text: Hello! |
|
example_title: Hello world |
|
group: Python |
|
--- |
|
|
|
This model is randomly initialized, using the config from [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) but with smaller size. |
|
|
|
Codes: |
|
```python |
|
from optimum.intel.openvino import OVModelForCausalLM |
|
from transformers import pipeline |
|
from huggingface_hub import create_repo, upload_folder |
|
import torch |
|
import transformers |
|
import os |
|
|
|
model_id = 'mistralai/Mistral-7B-v0.1' |
|
save_path = '/tmp/yujiepan/mistral-tiny-random' |
|
repo_id = 'yujiepan/mistral-tiny-random' |
|
|
|
config = transformers.AutoConfig.from_pretrained(model_id) |
|
config.hidden_size = 8 |
|
config.intermediate_size = 32 |
|
config.num_attention_heads = 4 |
|
config.num_hidden_layers = 2 |
|
config.num_key_value_heads = 2 |
|
print(config) |
|
|
|
tokenizer = transformers.AutoTokenizer.from_pretrained(model_id) |
|
tokenizer.save_pretrained(save_path) |
|
|
|
model = transformers.AutoModelForCausalLM.from_config(config, torch_dtype=torch.float16) |
|
model = model.half() |
|
|
|
pipe = pipeline('text-generation', model=model, tokenizer=tokenizer, do_sample=False, device='cuda') |
|
print(pipe('Hello World!')) |
|
|
|
model.save_pretrained(save_path) |
|
|
|
ovmodel = OVModelForCausalLM.from_pretrained(save_path, export=True) |
|
ovmodel = ovmodel.half() |
|
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) |
|
``` |
|
|
|
|
|
|