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| Property | Value |
|---|---|
| Layers | 5 |
| Hidden size | 192 |
| Intermediate size | 512 |
| Attention heads | 6 (GQA kv=6) |
| Max sequence length | 1024 |
| Vocab size | 4096 |
| Tied embeddings | True |
| Total parameters | 3.000M |
1from transformers import AutoTokenizer, AutoModelForCausalLM
2tokenizer = AutoTokenizer.from_pretrained("CyanMonkey/Exp-4")
3model = AutoModelForCausalLM.from_pretrained("CyanMonkey/Exp-4")
4inputs = tokenizer("Hello", return_tensors="pt")
5output = model.generate(**inputs, max_new_tokens=50)
6print(tokenizer.decode(output[0], skip_special_tokens=True))