LTX-Test-Renamed

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README

License: mit

Specs

Table
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

python
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:

python
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.

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