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navyam-ai
/
navya-1c-sft

Text Generation
Transformers
Safetensors
English
Hindi
llama
india
finance
from-scratch
navya
text-generation-inference
Model card Files
xet
 Community
How to use from
vLLM
Install from pip and serve model 
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "navyam-ai/navya-1c-sft"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "navyam-ai/navya-1c-sft",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker 
docker model run hf.co/navyam-ai/navya-1c-sft
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navya-1c-sft

Navya is an India-first financial foundation model family, trained from scratch on an India-first corpus (finance + English + Hindi/Hinglish and other Indian languages), custom 64k tokenizer.

Parameters 1.31B
Training tokens ~103B
Trained Sep 2026
Type chat (SFT)
Author Navyam AI (Bachatt)
License Apache-2.0
Code https://github.com/bachatt-app/navyam-gpt

1.31B base (~103B tokens + cooldown) then SFT on the India-finance corpus (val loss ~1.09). The model currently live on navyam.ai.

Intended use: India personal-finance Q&A. Research model — not investment advice.

Chat template

Role tokens <|reserved_0..4|> (system/user/assistant/tool/end_turn); generation stops on <|reserved_4|> and <|eos|>.

Usage 

from transformers import AutoModelForCausalLM, AutoTokenizer
tok = AutoTokenizer.from_pretrained("navyam-ai/navya-1c-sft")
model = AutoModelForCausalLM.from_pretrained("navyam-ai/navya-1c-sft")
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