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README.md CHANGED
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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # TinyStories-150M-Starter
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+
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+ This is a small decoder-only language model exported from the Kitsune Fine-Tuning Suite `Create` pipeline.
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+
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+ ## What This Export Is
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+
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+ - Architecture family for tooling compatibility: `LlamaForCausalLM`
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+ - Original project type: manual-first small transformer scaffold
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+ - Export source checkpoint: `final.pt`
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+
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+ ## Notes
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+
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+ This export is meant to behave like a normal Hugging Face causal LM checkpoint so it can be loaded by standard tooling.
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+ It was not originally trained as an off-the-shelf Llama release; it was mapped into a Llama-compatible layout for portability.
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+
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+ ## Training Context
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+
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+ - Dataset ID: `roneneldan/TinyStories`
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+ - Dataset Path: `None`
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+ - Train Split: `train`
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+ - Max Steps: `20000`
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+ - Learning Rate: `0.0003`
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+
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+ ## Example
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model_id = "hf_llama"
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+ tokenizer = AutoTokenizer.from_pretrained(model_id)
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+ model = AutoModelForCausalLM.from_pretrained(model_id)
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+ ```
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+ {
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ "attention_bias": false,
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+ "attention_dropout": 0.0,
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+ "hidden_act": "silu",
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+ "initializer_range": 0.02,
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+ "intermediate_size": 2048,
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+ "max_position_embeddings": 1024,
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+ "mlp_bias": false,
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+ "model_type": "llama",
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+ "num_hidden_layers": 12,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.55.4",
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+ "unk_token_id": 3,
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
export_meta.json ADDED
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+ {
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+ "status": "completed",
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+ "export_type": "hf_llama_compatible",
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+ "project_name": "TinyStories-150M-Starter",
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+ "checkpoint": "D:\\Ollama\\ollama_ui\\kitsune_training_suite\\training\\projects\\tinystories-150m-starter\\artifacts\\checkpoints\\final.pt",
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+ "out_dir": "D:\\Ollama\\ollama_ui\\kitsune_training_suite\\training\\projects\\tinystories-150m-starter\\artifacts\\exports\\hf_llama",
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+ "missing_keys": []
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+ }
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