Initial 4-bit MLX conversion of kenpath/svara-tts-v1
Browse files- .gitattributes +1 -0
- README.md +149 -0
- chat_template.jinja +93 -0
- config.json +47 -0
- model.safetensors +3 -0
- model.safetensors.index.json +656 -0
- tokenizer.json +3 -0
- tokenizer_config.json +16 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
ADDED
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@@ -0,0 +1,149 @@
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| 1 |
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---
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| 2 |
+
base_model: kenpath/svara-tts-v1
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| 3 |
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license: apache-2.0
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| 4 |
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language:
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- hi
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- bn
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- mr
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- te
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| 9 |
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- kn
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- bho
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- mag
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- hne
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- mai
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| 14 |
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- as
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- brx
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- doi
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- gu
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- ml
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- pa
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- ta
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- ne
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- sa
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- en
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tags:
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- text-to-speech
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- speech-synthesis
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- multilingual
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- indic
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- orpheus
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- snac
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- mlx
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- mlx-audio
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task_categories:
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- text-to-speech
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pipeline_tag: text-to-speech
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pretty_name: Svara-TTS v1 (MLX, 4-bit)
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datasets:
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- SYSPIN
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- RASA
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- IndicTTS
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- SPICOR
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library_name: mlx
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---
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# Svara-TTS v1 — MLX 4-bit
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4-bit MLX-quantized port of [`kenpath/svara-tts-v1`](https://huggingface.co/kenpath/svara-tts-v1) — an autoregressive multilingual text-to-speech model for 19 Indian languages, in the Orpheus / SNAC family. Quantized at **~4.5 bits per weight** (`q-bits=4`, `q-group-size=64`), down from ~13.2 GB bf16 to **~1.9 GB**.
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Built for [mlx-audio](https://github.com/Blaizzy/mlx-audio) on Apple Silicon.
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| 50 |
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## Usage
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| 52 |
+
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| 53 |
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Requires `mlx-audio` with TTS extras:
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| 54 |
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| 55 |
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```bash
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pip install "mlx-audio[tts]"
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| 57 |
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```
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| 59 |
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### Python
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| 60 |
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```python
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import numpy as np
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| 63 |
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import soundfile as sf
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| 64 |
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import mlx.core as mx
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| 65 |
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from mlx_audio.tts.utils import load_model
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| 66 |
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model = load_model("shreyask/svara-tts-v1-4bit")
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| 68 |
+
|
| 69 |
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chunks = []
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| 70 |
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for result in model.generate(
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| 71 |
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text="नमस्ते, आप कैसे हैं? मैं ठीक हूँ।",
|
| 72 |
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voice="Hindi (Female)",
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| 73 |
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temperature=0.75,
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top_p=0.9,
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top_k=40,
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| 76 |
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repetition_penalty=1.1,
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| 77 |
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max_tokens=1200,
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):
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| 79 |
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chunks.append(result.audio)
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| 80 |
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| 81 |
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audio = mx.concatenate(chunks, axis=0)
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| 82 |
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sf.write("hello_hi.wav", np.asarray(audio), model.sample_rate) # 24 kHz
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| 83 |
+
```
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| 84 |
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| 85 |
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### CLI
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| 86 |
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```bash
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mlx_audio.tts.generate \
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| 89 |
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--model shreyask/svara-tts-v1-4bit \
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| 90 |
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--text "नमस्ते, आप कैसे हैं?" \
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| 91 |
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--voice "Hindi (Female)" \
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| 92 |
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--temperature 0.75 \
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| 93 |
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--top_p 0.9
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| 94 |
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```
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| 95 |
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| 96 |
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## Voices
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| 97 |
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| 98 |
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Use a string of the form `"<Language Name> (<Gender>)"`:
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| 99 |
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| Language | Voices |
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| 101 |
+
|--------------|-------------------------------------|
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| 102 |
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| Hindi | `Hindi (Male)`, `Hindi (Female)` |
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| 103 |
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| Bengali | `Bengali (Male)`, `Bengali (Female)`|
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| 104 |
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| Marathi | `Marathi (Male)`, `Marathi (Female)`|
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| 105 |
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| Telugu | `Telugu (Male)`, `Telugu (Female)` |
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| Kannada | `Kannada (Male)`, `Kannada (Female)`|
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| 107 |
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| Tamil | `Tamil (Male)`, `Tamil (Female)` |
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| 108 |
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| Malayalam | `Malayalam (Male)`, `Malayalam (Female)` |
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| 109 |
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| Gujarati | `Gujarati (Male)`, `Gujarati (Female)` |
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| 110 |
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| Punjabi | `Punjabi (Male)`, `Punjabi (Female)` |
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| 111 |
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| Assamese | `Assamese (Male)`, `Assamese (Female)` |
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| 112 |
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| Bhojpuri | `Bhojpuri (Male)`, `Bhojpuri (Female)` |
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| Magahi | `Magahi (Male)`, `Magahi (Female)` |
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| Maithili | `Maithili (Male)`, `Maithili (Female)` |
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| 115 |
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| Chhattisgarhi| `Chhattisgarhi (Male)`, `Chhattisgarhi (Female)` |
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| 116 |
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| Bodo | `Bodo (Male)`, `Bodo (Female)` |
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| 117 |
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| Dogri | `Dogri (Male)`, `Dogri (Female)` |
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| 118 |
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| Nepali | `Nepali (Male)`, `Nepali (Female)` |
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| 119 |
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| Sanskrit | `Sanskrit (Male)`, `Sanskrit (Female)` |
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| 120 |
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| English (Indian) | `English (Indian) (Male)`, `English (Indian) (Female)` |
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| 121 |
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Total: **38 voices** across 19 languages.
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| 123 |
+
|
| 124 |
+
## Sampling Recommendations
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| 125 |
+
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| 126 |
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The upstream `svara-tts-inference` repo uses these defaults; they're a good starting point:
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| 127 |
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| 128 |
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| Parameter | Value |
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| 129 |
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|-----------|-------|
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| 130 |
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| `temperature` | 0.75 |
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| 131 |
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| `top_p` | 0.9 |
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| 132 |
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| `top_k` | 40 |
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| 133 |
+
| `repetition_penalty` | 1.1 |
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| 134 |
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| `max_tokens` | 1200–2048 |
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| 135 |
+
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| 136 |
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## Architecture
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| 137 |
+
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| 138 |
+
- **Backbone:** Llama-3.2-3B (fine-tuned from [`canopylabs/3b-hi-ft-research_release`](https://huggingface.co/canopylabs/3b-hi-ft-research_release), Canopy's Orpheus Hindi base).
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| 139 |
+
- **Codec:** [SNAC 24 kHz](https://huggingface.co/hubertsiuzdak/snac_24khz) — 3-level hierarchical RVQ, 7 codes per ~10 ms frame. Loaded automatically by `mlx-audio`.
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| 140 |
+
- **Output:** 24 kHz mono PCM.
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| 141 |
+
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| 142 |
+
## Other Quants
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| 143 |
+
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- 8-bit MLX: [`shreyask/svara-tts-v1-8bit`](https://huggingface.co/shreyask/svara-tts-v1-8bit) (~3.3 GB)
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| 145 |
+
- bf16 source: [`kenpath/svara-tts-v1`](https://huggingface.co/kenpath/svara-tts-v1) (~13.2 GB)
|
| 146 |
+
|
| 147 |
+
## License
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| 148 |
+
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| 149 |
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Apache 2.0 — see [base model card](https://huggingface.co/kenpath/svara-tts-v1) for full details.
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chat_template.jinja
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| 1 |
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{{- bos_token }}
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| 2 |
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{%- if custom_tools is defined %}
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| 3 |
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{%- set tools = custom_tools %}
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| 4 |
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{%- endif %}
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| 5 |
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{%- if not tools_in_user_message is defined %}
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| 6 |
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{%- set tools_in_user_message = true %}
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| 7 |
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{%- endif %}
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| 8 |
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{%- if not date_string is defined %}
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| 9 |
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{%- if strftime_now is defined %}
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| 10 |
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{%- set date_string = strftime_now("%d %b %Y") %}
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| 11 |
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{%- else %}
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| 12 |
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{%- set date_string = "26 Jul 2024" %}
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| 13 |
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{%- endif %}
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| 14 |
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{%- endif %}
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| 15 |
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{%- if not tools is defined %}
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| 16 |
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{%- set tools = none %}
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| 17 |
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{%- endif %}
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| 18 |
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| 19 |
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{#- This block extracts the system message, so we can slot it into the right place. #}
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| 20 |
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{%- if messages[0]['role'] == 'system' %}
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| 21 |
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{%- set system_message = messages[0]['content']|trim %}
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| 22 |
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{%- set messages = messages[1:] %}
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| 23 |
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{%- else %}
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| 24 |
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{%- set system_message = "" %}
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| 25 |
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{%- endif %}
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| 26 |
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| 27 |
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{#- System message #}
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| 28 |
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{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
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| 29 |
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{%- if tools is not none %}
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| 30 |
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{{- "Environment: ipython\n" }}
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| 31 |
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{%- endif %}
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| 32 |
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{{- "Cutting Knowledge Date: December 2023\n" }}
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| 33 |
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{{- "Today Date: " + date_string + "\n\n" }}
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| 34 |
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{%- if tools is not none and not tools_in_user_message %}
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| 35 |
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{{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
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| 36 |
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{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
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| 37 |
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{{- "Do not use variables.\n\n" }}
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| 38 |
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{%- for t in tools %}
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| 39 |
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{{- t | tojson(indent=4) }}
|
| 40 |
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{{- "\n\n" }}
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| 41 |
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{%- endfor %}
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| 42 |
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{%- endif %}
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| 43 |
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{{- system_message }}
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| 44 |
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{{- "<|eot_id|>" }}
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| 45 |
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| 46 |
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{#- Custom tools are passed in a user message with some extra guidance #}
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| 47 |
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{%- if tools_in_user_message and not tools is none %}
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| 48 |
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{#- Extract the first user message so we can plug it in here #}
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| 49 |
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{%- if messages | length != 0 %}
|
| 50 |
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{%- set first_user_message = messages[0]['content']|trim %}
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| 51 |
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{%- set messages = messages[1:] %}
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| 52 |
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{%- else %}
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| 53 |
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{{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
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| 54 |
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{%- endif %}
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| 55 |
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{{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
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| 56 |
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{{- "Given the following functions, please respond with a JSON for a function call " }}
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| 57 |
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{{- "with its proper arguments that best answers the given prompt.\n\n" }}
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| 58 |
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{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
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| 59 |
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{{- "Do not use variables.\n\n" }}
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| 60 |
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{%- for t in tools %}
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| 61 |
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{{- t | tojson(indent=4) }}
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| 62 |
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{{- "\n\n" }}
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| 63 |
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{%- endfor %}
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| 64 |
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{{- first_user_message + "<|eot_id|>"}}
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| 65 |
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{%- endif %}
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| 66 |
+
|
| 67 |
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{%- for message in messages %}
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| 68 |
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{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
|
| 69 |
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{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
|
| 70 |
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{%- elif 'tool_calls' in message %}
|
| 71 |
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{%- if not message.tool_calls|length == 1 %}
|
| 72 |
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{{- raise_exception("This model only supports single tool-calls at once!") }}
|
| 73 |
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{%- endif %}
|
| 74 |
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{%- set tool_call = message.tool_calls[0].function %}
|
| 75 |
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{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
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| 76 |
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{{- '{"name": "' + tool_call.name + '", ' }}
|
| 77 |
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{{- '"parameters": ' }}
|
| 78 |
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{{- tool_call.arguments | tojson }}
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| 79 |
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{{- "}" }}
|
| 80 |
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{{- "<|eot_id|>" }}
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| 81 |
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{%- elif message.role == "tool" or message.role == "ipython" %}
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| 82 |
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{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
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| 83 |
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{%- if message.content is mapping or message.content is iterable %}
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| 84 |
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{{- message.content | tojson }}
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| 85 |
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{%- else %}
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| 86 |
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{{- message.content }}
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| 87 |
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{%- endif %}
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| 88 |
+
{{- "<|eot_id|>" }}
|
| 89 |
+
{%- endif %}
|
| 90 |
+
{%- endfor %}
|
| 91 |
+
{%- if add_generation_prompt %}
|
| 92 |
+
{{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
|
| 93 |
+
{%- endif %}
|
config.json
ADDED
|
@@ -0,0 +1,47 @@
|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"LlamaForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_bias": false,
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"bos_token_id": 128000,
|
| 8 |
+
"eos_token_id": 128009,
|
| 9 |
+
"head_dim": 128,
|
| 10 |
+
"hidden_act": "silu",
|
| 11 |
+
"hidden_size": 3072,
|
| 12 |
+
"initializer_range": 0.02,
|
| 13 |
+
"intermediate_size": 8192,
|
| 14 |
+
"max_position_embeddings": 131072,
|
| 15 |
+
"mlp_bias": false,
|
| 16 |
+
"model_type": "llama",
|
| 17 |
+
"num_attention_heads": 24,
|
| 18 |
+
"num_hidden_layers": 28,
|
| 19 |
+
"num_key_value_heads": 8,
|
| 20 |
+
"pad_token_id": 128263,
|
| 21 |
+
"pretraining_tp": 1,
|
| 22 |
+
"quantization": {
|
| 23 |
+
"group_size": 64,
|
| 24 |
+
"bits": 4,
|
| 25 |
+
"mode": "affine"
|
| 26 |
+
},
|
| 27 |
+
"quantization_config": {
|
| 28 |
+
"group_size": 64,
|
| 29 |
+
"bits": 4,
|
| 30 |
+
"mode": "affine"
|
| 31 |
+
},
|
| 32 |
+
"rms_norm_eps": 1e-05,
|
| 33 |
+
"rope_scaling": {
|
| 34 |
+
"factor": 32.0,
|
| 35 |
+
"high_freq_factor": 4.0,
|
| 36 |
+
"low_freq_factor": 1.0,
|
| 37 |
+
"original_max_position_embeddings": 8192,
|
| 38 |
+
"rope_type": "llama3"
|
| 39 |
+
},
|
| 40 |
+
"rope_theta": 500000.0,
|
| 41 |
+
"tie_word_embeddings": true,
|
| 42 |
+
"torch_dtype": "bfloat16",
|
| 43 |
+
"transformers_version": "4.55.4",
|
| 44 |
+
"unsloth_version": "2025.10.4",
|
| 45 |
+
"use_cache": true,
|
| 46 |
+
"vocab_size": 156940
|
| 47 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d466a02dcffa81369fb151d3b108aea36f272b0e6b49530a9d9dbe0090fa57a9
|
| 3 |
+
size 1857062681
|
model.safetensors.index.json
ADDED
|
@@ -0,0 +1,656 @@
|
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|
|
|
| 1 |
+
{
|
| 2 |
+
"metadata": {
|
| 3 |
+
"total_size": 1856989440,
|
| 4 |
+
"total_parameters": 3300867072
|
| 5 |
+
},
|
| 6 |
+
"weight_map": {
|
| 7 |
+
"model.embed_tokens.biases": "model.safetensors",
|
| 8 |
+
"model.embed_tokens.scales": "model.safetensors",
|
| 9 |
+
"model.embed_tokens.weight": "model.safetensors",
|
| 10 |
+
"model.layers.0.input_layernorm.weight": "model.safetensors",
|
| 11 |
+
"model.layers.0.mlp.down_proj.biases": "model.safetensors",
|
| 12 |
+
"model.layers.0.mlp.down_proj.scales": "model.safetensors",
|
| 13 |
+
"model.layers.0.mlp.down_proj.weight": "model.safetensors",
|
| 14 |
+
"model.layers.0.mlp.gate_proj.biases": "model.safetensors",
|
| 15 |
+
"model.layers.0.mlp.gate_proj.scales": "model.safetensors",
|
| 16 |
+
"model.layers.0.mlp.gate_proj.weight": "model.safetensors",
|
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+
}
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:044e2a10201774018db120391980464472baabf223bd353cea49b17da0b66abc
|
| 3 |
+
size 22849546
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,16 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"backend": "tokenizers",
|
| 3 |
+
"bos_token": "<|begin_of_text|>",
|
| 4 |
+
"clean_up_tokenization_spaces": true,
|
| 5 |
+
"eos_token": "<|eot_id|>",
|
| 6 |
+
"is_local": true,
|
| 7 |
+
"local_files_only": false,
|
| 8 |
+
"model_input_names": [
|
| 9 |
+
"input_ids",
|
| 10 |
+
"attention_mask"
|
| 11 |
+
],
|
| 12 |
+
"model_max_length": 131072,
|
| 13 |
+
"pad_token": "<custom_token_7>",
|
| 14 |
+
"padding_side": "right",
|
| 15 |
+
"tokenizer_class": "TokenizersBackend"
|
| 16 |
+
}
|