This model is for debugging. It is randomly initialized using the config from HuggingFaceTB/SmolLM-1.7B but with smaller size.
Codes:
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))