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Building on HF
2
2
12
Pankaj Pandey
pankajpandey-dev
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pankajpandey-dev
pankajpandey-dev
AI & ML interests
Natural Language Processing, Text Generation, Large Language Models, Quantization, Fine-Tuning, RLHF, Model Merging
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🇮🇳 Gemma-3-1B Hindi Instruct — a Hindi LLM that runs fully offline, anywhere. Last week I shipped Qwen3-4B Hindi. This week I went the other direction: how tiny can a useful Hindi model get? So I fine-tuned Gemma-3-1B on quality-filtered Hindi instruction data and shipped the full GGUF ladder. ✅ Fine-tune (16-bit): https://huggingface.co/pankajpandey-dev/gemma-3-1b-hindi-instruct ✅ GGUF (Q4/Q5/Q8): https://huggingface.co/pankajpandey-dev/gemma-3-1b-hindi-instruct-GGUF Runs in Ollama, llama.cpp, and LM Studio. The Q4_K_M is just 806 MB — runs on CPU, a cheap laptop, even a Raspberry Pi. What I tried this round: chrF-filtered the training data to drop weak translations, and used response-only loss so the model learns how to answer, not how to repeat prompts. Honest note: at 1B, Hindi fluency is strong but coherence is bounded by size — it's a lightweight/edge experiment, not a 4B replacement. Gemma-3-4B Hindi is next. Part of my Hindi LLM Series — openly-licensed Indic models for local & edge use. Feedback welcome 🙏 #Hindi #IndicNLP #GGUF #LocalLLM #Gemma #EdgeAI
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pankajpandey-dev/qwen3-4b-hindi-demo
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