model-name

A tiny, randomly-initialized GPT-2-style model for testing tooling and pipelines. It is not trained — outputs are meaningless. The point is a small, valid Hugging Face layout (config.json + model.safetensors) that real loaders accept.

Specs

Field	Value
Architecture	GPT2LMHeadModel
Params	~43.9K
Hidden size	32
Layers	2
Heads	4
Vocab	256
Context	64
dtype	float32
Weights file	model.safetensors (~174 KiB)

Usage

from transformers import AutoModelForCausalLM
import torch

model = AutoModelForCausalLM.from_pretrained(".")
out = model(torch.zeros(1, 8, dtype=torch.long))
print(out.logits.shape)  # torch.Size([1, 8, 256])

Or load the raw tensors directly:

from safetensors.torch import load_file
state = load_file("model.safetensors")
print(len(state), "tensors")

Notes

• Weights are random (torch.manual_seed(0), init range 0.02); LayerNorm/biases use the conventional ones/zeros init.
• Intended for CI, smoke tests, and verifying upload/download plumbing — do not use for inference quality.