AI for Nepal
Models built for Nepal, served by Tarka.
Call HimalayaAI’s Nepali language, OCR and speech models through one OpenAI-compatible API. If you’re building a model for Nepal, Tarka can host and serve it alongside them.
Start with HimalayaAI’s models.
HimalayaAI is a research lab that trains open-source Nepali AI models and publishes Nepali datasets and benchmarks. Four of its models run on Tarka, next to a community model for Nepali speech recognition.
| Published by | Model | Type | Model IDs | Source |
|---|---|---|---|---|
| HimalayaAI | HimalayaGPT 0.5B A compact, Nepali-first instruction model. | Language model | himalaya-q4himalaya-q8himalaya-bf16 | Hugging Face |
| HimalayaAI | Himalaya Gemma 4 E2B A larger Nepali–English instruction model based on Gemma 4 E2B. | Language model | himalaya-gemma-4-q4himalaya-gemma-4-q8himalaya-gemma-4-bf16 | Hugging Face |
| HimalayaAI | GLM OCR Devanagari GLM-OCR fine-tuned to read text from Devanagari documents. | Document OCR | glm-ocr-nepali | Hugging Face |
| HimalayaAI | Nepali Parler TTS Indic Parler-TTS fine-tuned for Nepali. Describe the voice you want in words. | Text to speech | nepali-parler-tts | Hugging Face |
| lilgoose777 | Whisper Medium Nepali Whisper Medium for Nepali transcription, as a CTranslate2 build. | Speech to text | whisper-nepali-medium | Hugging Face |
Tarka keeps the inputs and outputs of HimalayaGPT and Himalaya Gemma requests for evaluation and debugging, not for training. Their model IDs ending in -private skip this; each model’s page lists them.
Make your first request.
Each example is the OpenAI Python client pointed at Tarka. Only the method and the model ID change.
Create an account
Sign up in the console and request HimalayaAI models and Utility models.
Create an API key
Give it the same model categories. It is shown once, so store it somewhere safe.
Call a model
Use a model ID from this page.
GET /v1/modelslists the ones your key can call.
from openai import OpenAI
client = OpenAI(
base_url="https://tarka.rest/v1",
api_key="tk_live_xxx",
)
prompt = "नेपालबारे कविता लेख्नुहोस्।"
chat = client.chat.completions.create(
model="himalaya-q8",
messages=[{"role": "user",
"content": prompt}],
)
print(chat.choices[0].message.content)
from openai import OpenAI
client = OpenAI(
base_url="https://tarka.rest/v1",
api_key="tk_live_xxx",
)
with open("voice-note.wav", "rb") as audio:
result = client.audio.transcriptions.create(
model="whisper-nepali-medium",
file=audio, language="ne",
)
print(result.text)
from openai import OpenAI
client = OpenAI(
base_url="https://tarka.rest/v1",
api_key="tk_live_xxx",
)
speech = client.audio.speech.create(
model="nepali-parler-tts",
voice="A clear, calm Nepali speaker",
input="नमस्ते नेपाल", response_format="wav",
)
speech.write_to_file("namaste.wav")
Host your Nepali model on Tarka.
If you’ve trained or fine-tuned a Nepali language, speech or document model and its license allows hosting, Tarka can serve it through the same API as the models above.
- Send us the modelA Hugging Face repository or the weights, the license they’re released under, and a few example inputs with the outputs you expect.
- Tarka sets it up and tests itTarka’s engineers deploy the weights and check the output against your examples before it goes live.
- Developers call itIt gets a model ID on the Tarka API and a row in the table above, credited to you. Any account with access to that type of model can call it.
Tell us about your model.
Send a link to the model and a line on what it’s for.