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README.md

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+
+---
+
+datasets:
+- homebrewltd/instruction-speech-whispervq-v2
+language:
+- en
+license: apache-2.0
+tags:
+- sound language model
+
+---
+
+![](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)
+
+# QuantFactory/llama3.1-s-base-v0.2-GGUF
+This is quantized version of [homebrewltd/llama3.1-s-base-v0.2](https://huggingface.co/homebrewltd/llama3.1-s-base-v0.2) created using llama.cpp
+
+# Original Model Card
+
+
+## Model Details
+
+We have developed and released the family [llama3s](https://huggingface.co/collections/homebrew-research/llama3-s-669df2139f0576abc6eb7405). This family is natively understanding audio and text input.
+
+We continual pretrain on the expanded vocabulary [homebrewltd/llama3.1-s-whispervq-init](https://huggingface.co/homebrewltd/llama3.1-s-whispervq-init) with 900M tokens from [homebrewltd/raw-speech-whispervq-v1](https://huggingface.co/datasets/homebrewltd/raw-speech-whispervq-v1) dataset.
+
+**Model developers** Homebrew Research.
+
+**Input** Text and sound.
+
+**Output** Text.
+
+**Model Architecture** Llama-3.
+
+**Language(s):** English.
+
+## Intended Use
+
+**Intended Use Cases** This family is primarily intended for research applications. This version aims to further improve the LLM on sound understanding capabilities.
+
+**Out-of-scope** The use of llama3-s in any manner that violates applicable laws or regulations is strictly prohibited.
+
+## Training process
+**Training Metrics Image**: Below is a snapshot of the training loss curve visualized.
+
+![train_log](https://cdn-uploads.huggingface.co/production/uploads/65713d70f56f9538679e5a56/iAbaP7SCoyZ8tz2hyK8k0.png)
+
+### Hardware
+
+**GPU Configuration**: Cluster of 10x NVIDIA A6000-48GB.
+
+**GPU Usage**:
+  - **Continual Training**: 30 hours.
+
+### Training Arguments
+
+We utilize [torchtune](https://github.com/pytorch/torchtune) library for the latest FSDP2 training code implementation. 
+
+| Parameter                  | Continual Training      | 
+|----------------------------|-------------------------|
+| **Epoch**                  | 1                       | 
+| **Global batch size**      | 480                     | 
+| **Learning Rate**          | 2e-4                    | 
+| **Learning Scheduler**     | Cosine with warmup      | 
+| **Optimizer**              | AdamW fused             | 
+| **Warmup Steps**           | 50                      | 
+| **Weight Decay**           | 0.01                    |
+| **Max Sequence Length**    | 512                     |
+
+
+## Citation Information
+
+**BibTeX:**
+
+```
+@article{Llama3-S: Sound Instruction Language Model 2024,
+  title={Llama3-S},
+  author={Homebrew Research},
+  year=2024,
+  month=August},
+  url={https://huggingface.co/homebrewltd/llama3.1-s-2024-08-15}
+```
+
+## Acknowledgement
+
+- **[WhisperSpeech](https://github.com/collabora/WhisperSpeech)**
+
+- **[Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct)**