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@@ -42,6 +42,7 @@ This model is a fine-tuned variant of the EleutherAI/pythia-1b causal language m
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  - **Use Cases:** Integration into chat applications, developer portals, knowledge retrieval systems, and automated support bots.
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  **Out-of-Scope:**
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@@ -104,15 +105,6 @@ After 16 epochs, the training process yielded the following key outcomes:
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  - **Training Throughput:** 3.78 samples/sec, 0.47 steps/sec
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  - **Total FLOPs:** 2.72×10¹⁶
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- | Metric | Value |
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- |--------------------|------------|
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- | Final Train Loss | 0.03725 |
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- | Eval Loss (best) | *See logs* |
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- | Training Steps | 1,216 |
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- | Training Time | 2,572.28 s |
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- | Samples/sec | 3.78 |
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- | Steps/sec | 0.47 |
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  ## Limitations & Biases
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  - Although highly accurate on InferenceVision topics, the model may generate plausible but incorrect or outdated information if presented with out-of-distribution queries.
 
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  - **Use Cases:** Integration into chat applications, developer portals, knowledge retrieval systems, and automated support bots.
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+ For a hands-on guide on fine-tuning and using this model with **InferenceVision**, check out the [interactive notebook](https://github.com/doguilmak/InferenceVision/blob/main/usage/InferenveVision_LLM_QA.ipynb).
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  **Out-of-Scope:**
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  - **Training Throughput:** 3.78 samples/sec, 0.47 steps/sec
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  - **Total FLOPs:** 2.72×10¹⁶
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  ## Limitations & Biases
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  - Although highly accurate on InferenceVision topics, the model may generate plausible but incorrect or outdated information if presented with out-of-distribution queries.