README.md

---
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 [ai21labs/Jamba-v0.1](https://huggingface.co/ai21labs/Jamba-v0.1/blob/main/config.json) but with smaller size. 
Note the model is in float16.

Codes:
```python
import transformers
import torch
import os
from huggingface_hub import create_repo, upload_folder

source_model_id = 'ai21labs/Jamba-v0.1'
save_path = '/tmp/yujiepan/jamba-tiny-random'
repo_id = 'yujiepan/jamba-tiny-random'

config = transformers.AutoConfig.from_pretrained(
    source_model_id, trust_remote_code=True)
config.hidden_size = 4
config.intermediate_size = 6
config.num_attention_heads = 4
config.num_hidden_layers = 16
config.num_key_value_heads = 2
config.use_mamba_kernels = False

model = transformers.AutoModelForCausalLM.from_config(
    config, trust_remote_code=True)
model = model.half()
model.save_pretrained(save_path)

tokenizer = transformers.AutoTokenizer.from_pretrained(
    source_model_id, trust_remote_code=True)
tokenizer.save_pretrained(save_path)

result = transformers.pipelines.pipeline(
    'text-generation',
    model=model.float(), tokenizer=tokenizer)('Hello World!')
print(result)

os.system(f'ls -alh {save_path}')
create_repo(repo_id, exist_ok=True)
upload_folder(repo_id=repo_id, folder_path=save_path)
```