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Model: haykgrigorian/TimeCapsuleLLM-v2mini-eval2-llama-200m Source: Original Platform
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README.md
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license: mit
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datasets:
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- haykgrigorian/TimeCapsuleLLM-London-1800-1875-v2-15GB
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language:
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- en
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pipeline_tag: text-generation
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library_name: transformers
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---
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# haykgrigorian/v2mini-eval2: Llama-Architecture 215M Model
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## Model Overview
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**v2mini-eval2** model, trained from scratch on 15GB of 1800-1875 london texts using Llama architecture. This model was trained to validate the tokenizer before scaling to 90GB.
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| Detail | Value |
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| :--- | :--- |
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| **Model Architecture** | LlamaForCausalLM (Decoder-Only Transformer) |
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| **Parameter Count** | **~215 Million (214.8M)** |
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| **Training Type** | Trained **from Scratch** (10,000 steps) |
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| **Tokenizer** | Custom BPE, Vocab Size 32,003 |
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| **Sequence Length** | 4096 tokens (4x increase from eval1) |
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| **Attention Type** | Grouped Query Attention (GQA) |
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## Configuration Details
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eval2 uses a different configuration comapared to eval1 for extended context length:
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| Parameter | Value |
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| :--- | :--- |
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| **Number of Layers** | 24 |
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| **Hidden Size (d)** | 768 |
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| **Intermediate Size ($\text{d}_{\text{ff}}$)** | 2048 |
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| **Attention Heads** | 12 (Query) / 6 (Key/Value) |
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| **Activation Function** | SiLU (`silu`) |
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| **Normalization** | RMS Norm (`rms_norm_eps`: 1e-05) |
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| **Position Embeddings** | RoPE (Theta: 10,000) |
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## Improvements & Fixes
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* **Fixed Tokenization:** There was a spacing issue in the output from `eval1` (e.g., "D oes t ha t wor k") It's fixed now. Output should look normal.
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## Cost
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Total time in RunPod VM: 7:28
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Total time spent on training: 5:52
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A100 SXM Cost: $1.49/Hour
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Total cost: $11.12
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### How to Load and Run the Model
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Install all the files locally in a folder and run the test script. You will have to make some adjustments in the run script like updating the config/file path and test prompts
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### Test script
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A run file for testing and evaluating this model is available on the main project repository:
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* **Test Script Link:** [test_v2mini_eval2.py on GitHub](https://github.com/haykgrigo3/TimeCapsuleLLM/blob/main/london_1800_1875_v2mini_eval1/test_v2mini_eval2.py)
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