This model is for debugging. It is randomly initialized with the config from microsoft/phi-4 but is of smaller size.

Codes:

import os

import torch
import transformers
from transformers import (AutoConfig, AutoModelForCausalLM, AutoTokenizer,
                          GenerationConfig, pipeline, set_seed)

model_id = "microsoft/phi-4"
repo_id = "yujiepan/phi-4-tiny-random"
save_path = f"/tmp/{repo_id}"

config = AutoConfig.from_pretrained(model_id, trust_remote_code=True)
config.hidden_size = 16
config.intermediate_size = 32
config.num_attention_heads = 2
config.num_hidden_layers = 2
config.num_key_value_heads = 1

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

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

set_seed(42)
with torch.no_grad():
    for name, p in sorted(model.named_parameters()):
        torch.nn.init.normal_(p, 0, 0.5)
        print(name, p.shape)

model.save_pretrained(save_path)

pipe = pipeline("text-generation", model=save_path, device="cuda",
                trust_remote_code=True, max_new_tokens=20)
print(pipe("Hello World!"))
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3.22M params
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