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

This model is for debugging. It is randomly initialized using the config from [HuggingFaceTB/SmolLM-1.7B](https://huggingface.co/HuggingFaceTB/SmolLM-1.7B) but with smaller size. 

Codes:
```python
from huggingface_hub import create_repo, upload_folder
from transformers import (
    pipeline,
    set_seed,
    AutoConfig,
    AutoModelForCausalLM,
    AutoTokenizer,
    GenerationConfig,
)
import torch
import transformers
import os

model_id = "HuggingFaceTB/SmolLM-1.7B"
repo_id = "yujiepan/smollm-tiny-random"
save_path = f"/tmp/{repo_id}"

config = AutoConfig.from_pretrained(model_id, trust_remote_code=True)
config._name_or_path = model_id
config.hidden_size = 8
config.intermediate_size = 16
config.num_attention_heads = 4
config.num_hidden_layers = 2
config.num_key_value_heads = 2
print(config)

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

model = AutoModelForCausalLM.from_config(
    config, torch_dtype=torch.bfloat16, attn_implementation="eager", trust_remote_code=True
)
model.generation_config = GenerationConfig.from_pretrained(model_id, trust_remote_code=True)

set_seed(42)
with torch.no_grad():
    for _, p in sorted(model.named_parameters()):
        torch.nn.init.uniform_(p, -0.1, 0.1)

model.save_pretrained(save_path)

pipe = pipeline("text-generation", model=save_path, device="cuda", trust_remote_code=True)
print(pipe("Hello World!"))

# messages = [
#     {"role": "system", "content": "You are a robot."},
#     {"role": "user", "content": "Hi!"},
# ]
# chatbot = pipeline("text-generation", model=save_path, max_length=1000, max_new_tokens=16, trust_remote_code=True)
# print(chatbot(messages))
```