AI NEWS.ccLlama-3.2-0.5B-Instruct
This model uses a single `model.safetensors` file containing all weights. The checkpoint structure is identical to the original model, with the standard Llama architecture tensors: - `model.embed_tokens.weight` - `model.layers.*.self_attn.{q,k,v,o}_proj.weight` - `model.layers.*.mlp.{gate,up,down}_proj.weight` - `model.layers.*.{input,post_attention}_layernorm.weight` - `model.norm.weight` 1. Inspected the original model configuration to identify key parameters 2. Created a tiny version by reducing `num_hidden_layers` from 16 to 4 3. Fine-tuned the model on a toy dataset (famous copypastas) to validate learning capability 4. Achieved target perplexity of ~1.02 on the validation text 5. Validated checkpoint structure matches the original model format 6. Confirmed successful loading and inference
This model uses a single `model.safetensors` file containing all weights. The checkpoint structure is identical to the original model, with the standard Llama architecture tensors: - `model.embed_tokens.weight` - `model.layers.*.self_attn.{q,k,v,o}_proj.weight` - `model.layers.*.mlp.{gate,up,down}_proj.weight` - `model.layers.*.{input,post_attention}_layernorm.weight` - `model.norm.weight` 1. Inspected the original model configuration to identify key parameters 2. Created a tiny version by reducing `num_hidden_layers` from 16 to 4 3. Fine-tuned the model on a toy dataset (famous copypastas) to validate learning capability 4. Achieved target perplexity of ~1.02 on the validation text 5. Validated checkpoint structure matches the original model format 6. Confirmed successful loading and inference