```python
from sparseml.transformers import SparseAutoModelForCausalLM, SparseAutoTokenizer

ORIG_MODEL_PATH = "neuralmagic/TinyLlama-1.1B-Chat-v1.0-pruned2.4"
OUTPUT_PATH = "./compress_output"
HF_MODEL_ID = "mgoin/TinyLlama-1.1B-Chat-v1.0-pruned2.4-compressed"

# Compress and export the model
model = SparseAutoModelForCausalLM.from_pretrained(ORIG_MODEL_PATH, device_map="auto", torch_dtype="auto")
tokenizer = SparseAutoTokenizer.from_pretrained(ORIG_MODEL_PATH)

model.save_pretrained(OUTPUT_PATH, save_compressed=True)
tokenizer.save_pretrained(OUTPUT_PATH)

# Upload the checkpoint to Hugging Face
from huggingface_hub import HfApi
HfApi().upload_folder(
    folder_path=OUTPUT_PATH,
    repo_id=HF_MODEL_ID,
)
```