Duplicate from kenpath/svara-tts-v1

Co-authored-by: Aditya Chhabra <adityachhabra@users.noreply.huggingface.co>

.gitattributes

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+examples/chat[[:space:]]-[[:space:]]magahi.wav filter=lfs diff=lfs merge=lfs -text
+examples/clear[[:space:]]-[[:space:]]telugu.wav filter=lfs diff=lfs merge=lfs -text
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+examples/neutral[[:space:]]-[[:space:]]nepali.wav filter=lfs diff=lfs merge=lfs -text
+examples/neutral[[:space:]]-[[:space:]]sanskrit.wav filter=lfs diff=lfs merge=lfs -text
+examples/sad[[:space:]]-[[:space:]]malayalam.wav filter=lfs diff=lfs merge=lfs -text
+examples/sad[[:space:]]-[[:space:]]marathi.wav filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+base_model: canopylabs/3b-hi-ft-research_release
+license: apache-2.0
+language:
+- hi   # Hindi
+- bn   # Bengali
+- mr   # Marathi
+- te   # Telugu
+- kn   # Kannada
+- bho  # Bhojpuri
+- mag  # Magahi
+- hne  # Chhattisgarhi
+- mai  # Maithili
+- as   # Assamese
+- brx  # Bodo
+- doi  # Dogri
+- gu   # Gujarati
+- ml   # Malayalam
+- pa   # Punjabi
+- ta   # Tamil
+- ne   # Nepali
+- sa   # Sanskrit
+- en   # English (Indian)
+tags:
+- text-to-speech
+- speech-synthesis
+- transformers
+- multilingual
+- indic
+- orpheus
+- lora
+- low-latency
+- gguf
+- zero-shot
+- emotions
+- discrete-audio-tokens
+task_categories:
+- text-to-speech
+pipeline_tag: text-to-speech
+pretty_name: Svara-TTS v1
+datasets:
+- SYSPIN
+- RASA
+- IndicTTS
+- SPICOR
+---
+
+# svara-TTS v1 — Open Multilingual TTS for India’s Voices
+
+[![🤗 Hugging Face - svara-tts-v1 Model](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Model-black)](https://huggingface.co/kenpath/svara-tts-v1) 
+[![🤗 Hugging Face - Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-green)](https://huggingface.co/spaces/kenpath/svara-tts)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/15YxFo1DzdQNbFUIZ1HJA4AN4oHqKxGtg)
+[![GitHub](https://img.shields.io/badge/github-%23121011.svg?style=flat&logo=github&logoColor=white)](https://github.com/Kenpath/svara-tts-inference)
+
+**svara-TTS** is a developer-first multilingual TTS model for **19 languages** (18 Indic + Indian English).  
+Built on an Orpheus-style discrete audio token approach, it targets **clarity, expressiveness, and low-latency** on commodity GPUs/CPUs.  
+It supports light-weight **emotion/style control** (e.g., `<happy>`, `<sad>`, `<anger>`, `<fear>`) and simple **speaker identities** (`Language (Gender)`), with **zero-shot** adaptation paths.
+
+---
+
+## At a Glance
+
+- **Languages (19):** Hindi, Bengali, Marathi, Telugu, Kannada, Bhojpuri, Magahi, Chhattisgarhi, Maithili, Assamese, Bodo, Dogri, Gujarati, Malayalam, Punjabi, Tamil, Nepali, Sanskrit, Indian English.  
+- **Expressivity:** End-of-utterance style tags; natural prosody; code-switch aware.  
+- **Latency & Deployment:** Works well with **GGUF** exports; suitable for edge/CPU scenarios.  
+- **Adaptability:** **LoRA-friendly** for quick speaker/domain specialization.
+
+Try it live on the [**Demo Space**](https://huggingface.co/spaces/kenpath/svara-tts), or on **[Colab](https://colab.research.google.com/drive/15YxFo1DzdQNbFUIZ1HJA4AN4oHqKxGtg)**
+Deployment scripts and **inference repo** will be available soon. Watch our [Github](https://github.com/Kenpath/svara-tts-inference) for updates
+
+---
+
+## Prompting (Orpheus-style)
+
+- Place style/emotion tags **at the end** of the sentence:  
+  `आज... सच में अच्छी खबर है — शाम को मिलते हैं! <happy>`
+- Use punctuation to hint prosody (ellipses, commas, exclamation).
+- For technical or dense text, end with `<clear>` to prioritize intelligibility.
+
+> Speaker IDs follow a simple convention: **`Language (Gender)`** (e.g., `Marathi (Male)`).
+
+---
+
+## Training Data Summary
+
+Trained on **2000+ hours** of open, high-quality speech from **SYSPIN**, **RASA**, **IndicTTS**, and **SPICOR**, covering **~50 speakers** (balanced male/female) across **19 languages**.  
+Data was curated to encourage natural prosody, broad coverage, and stable multilingual transfer. See **Acknowledgments** for provenance.
+
+---
+
+## Intended Uses
+
+- Multilingual assistants, IVR, learning apps, reading aids, accessibility tools  
+- Content localization (education, public-information, civic services)  
+- Research on Indic prosody, emotion control, cross-lingual transfer
+
+## Out-of-Scope / Not Intended
+
+- Impersonation of private individuals or public figures without consent  
+- Deceptive content (fraud, harassment, misinformation)  
+- Safety-critical deployments without human oversight
+
+---
+
+## Limitations
+
+- **Proper nouns & rare entities:** may require spelling hints or `<clear>`.  
+- **Very long sentences:** chunk or add punctuation for natural prosody.  
+- **Emotion strength:** varies by language due to data density.  
+- **Code-mixing:** common patterns work; it’s not a deterministic rules engine.
+
+Many of these improve with targeted LoRA finetuning and better preprocessing.
+
+---
+
+## Responsible Use
+
+By using this model, you agree to follow applicable laws and ethical guidelines.  
+Avoid impersonation, harassment, targeted deception, or other harmful uses.  
+Where appropriate, disclose synthetic speech to end users.
+
+---
+
+## Sources & Links
+
+- **Model:** https://huggingface.co/kenpath/svara-tts-v1  
+- **Demo Space:** https://huggingface.co/spaces/kenpath/svara-tts  
+- **Inference repo:** https://github.com/Kenpath/svara-tts-inference  
+- **Colab:** https://colab.research.google.com/drive/15YxFo1DzdQNbFUIZ1HJA4AN4oHqKxGtg
+
+---
+
+## 🙏 Acknowledgments
+
+This work was developed by **[Kenpath Technologies](https://kenpath.ai/)** for the open-source community. We also thank RunPod for the startup credits that supported our GPU compute.
+
+- **Canopy Labs — Orpheus:** foundational ideas & open release  
+  Release: https://canopylabs.ai/releases/orpheus_can_speak_any_language  
+- **SPIRE Lab, IISc Bangalore** — **SYSPIN** (multilingual studio) and **SPICOR** (Indian English)  
+- **AI4Bharat** — **RASA** expressive speech  
+- **IIT Madras** — **IndicTTS**  
+- **Unsloth** — helpful notes & tooling  
+- **RunPod** — startup GPU credits that accelerated experiments
+
+---
+
+## License
+
+**Apache-2.0**
+
+---
+
+## Versioning & Changelog
+
+- **v1.0.0:** Initial public release (19 languages)

chat_template.jinja

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+{{- bos_token }}
+{%- if custom_tools is defined %}
+    {%- set tools = custom_tools %}
+{%- endif %}
+{%- if not tools_in_user_message is defined %}
+    {%- set tools_in_user_message = true %}
+{%- endif %}
+{%- if not date_string is defined %}
+    {%- if strftime_now is defined %}
+        {%- set date_string = strftime_now("%d %b %Y") %}
+    {%- else %}
+        {%- set date_string = "26 Jul 2024" %}
+    {%- endif %}
+{%- endif %}
+{%- if not tools is defined %}
+    {%- set tools = none %}
+{%- endif %}
+
+{#- This block extracts the system message, so we can slot it into the right place. #}
+{%- if messages[0]['role'] == 'system' %}
+    {%- set system_message = messages[0]['content']|trim %}
+    {%- set messages = messages[1:] %}
+{%- else %}
+    {%- set system_message = "" %}
+{%- endif %}
+
+{#- System message #}
+{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
+{%- if tools is not none %}
+    {{- "Environment: ipython\n" }}
+{%- endif %}
+{{- "Cutting Knowledge Date: December 2023\n" }}
+{{- "Today Date: " + date_string + "\n\n" }}
+{%- if tools is not none and not tools_in_user_message %}
+    {{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+{%- endif %}
+{{- system_message }}
+{{- "<|eot_id|>" }}
+
+{#- Custom tools are passed in a user message with some extra guidance #}
+{%- if tools_in_user_message and not tools is none %}
+    {#- Extract the first user message so we can plug it in here #}
+    {%- if messages | length != 0 %}
+        {%- set first_user_message = messages[0]['content']|trim %}
+        {%- set messages = messages[1:] %}
+    {%- else %}
+        {{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
+{%- endif %}
+    {{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
+    {{- "Given the following functions, please respond with a JSON for a function call " }}
+    {{- "with its proper arguments that best answers the given prompt.\n\n" }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+    {{- first_user_message + "<|eot_id|>"}}
+{%- endif %}
+
+{%- for message in messages %}
+    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
+        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
+    {%- elif 'tool_calls' in message %}
+        {%- if not message.tool_calls|length == 1 %}
+            {{- raise_exception("This model only supports single tool-calls at once!") }}
+        {%- endif %}
+        {%- set tool_call = message.tool_calls[0].function %}
+        {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+        {{- '{"name": "' + tool_call.name + '", ' }}
+        {{- '"parameters": ' }}
+        {{- tool_call.arguments | tojson }}
+        {{- "}" }}
+        {{- "<|eot_id|>" }}
+    {%- elif message.role == "tool" or message.role == "ipython" %}
+        {{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
+        {%- if message.content is mapping or message.content is iterable %}
+            {{- message.content | tojson }}
+        {%- else %}
+            {{- message.content }}
+        {%- endif %}
+        {{- "<|eot_id|>" }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128009,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 3072,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 24,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 8,
+  "pad_token_id": 128263,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 32.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.55.4",
+  "unsloth_version": "2025.10.4",
+  "use_cache": true,
+  "vocab_size": 156940
+}

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+    "model.layers.9.post_attention_layernorm.weight": "model-00002-of-00003.safetensors",
+    "model.layers.9.self_attn.k_proj.weight": "model-00002-of-00003.safetensors",
+    "model.layers.9.self_attn.o_proj.weight": "model-00002-of-00003.safetensors",
+    "model.layers.9.self_attn.q_proj.weight": "model-00002-of-00003.safetensors",
+    "model.layers.9.self_attn.v_proj.weight": "model-00002-of-00003.safetensors",
+    "model.norm.weight": "model-00003-of-00003.safetensors"
+  }
+}

special_tokens_map.json

@@ -0,0 +1,20 @@
+{
+  "additional_special_tokens": [
+    "<|audio|>"
+  ],
+  "bos_token": {
+    "content": "<|begin_of_text|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|eot_id|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<custom_token_7>"
+}

tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:044e2a10201774018db120391980464472baabf223bd353cea49b17da0b66abc
+size 22849546