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license: apache-2.0 |
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--- |
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Here is a code to create this tiny model: |
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```python |
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import os |
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import torch |
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torch.set_default_dtype(torch.bfloat16) |
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from transformers import AutoTokenizer, AutoConfig, Lfm2ForCausalLM |
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# # === Step 1: Define tiny model config === |
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model_id = "LiquidAI/LFM2-350M" |
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config = AutoConfig.from_pretrained(model_id) |
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config.num_hidden_layers=4 |
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config.layer_types=[ |
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"conv", |
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"conv", |
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"full_attention", |
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"conv", |
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] |
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config.num_attention_heads=4 |
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config.num_key_value_heads=4 |
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config.hidden_size=16 |
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config.block_multiple_of=8 |
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# === Step 2: Create model from config === |
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model = Lfm2ForCausalLM(config) |
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# === Step 3: Load or create tokenizer === |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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# === Step 4: Save model and tokenizer === |
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output_dir = "./lfm2" |
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os.makedirs(output_dir, exist_ok=True) |
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model.save_pretrained(output_dir, safe_serialization=False) |
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tokenizer.save_pretrained(output_dir) |
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``` |
