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Pankaj Pandey

pankajpandey-dev
keke-420's profile picture or99's profile picture gpancardo's profile picture
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AI & ML interests

Natural Language Processing, Text Generation, Large Language Models, Quantization, Fine-Tuning, RLHF, Model Merging.

Recent Activity

reacted to theirpost with ❤️ about 4 hours ago
🇮🇳 New in my Hindi LLM Series: Gemma-4 E4B, fine-tuned for Hindi — and it runs on your laptop's CPU. I fine-tuned Google's new Gemma-4 E4B on ~10k Hindi instruction pairs (AI4Bharat: anudesh + dolly) using Unsloth + LoRA, on a single L4 GPU. Then I ran an honest side-by-side eval: base Gemma-4 vs my fine-tune, across 25 Hindi prompts. The results were interesting 👇 ✅ My fine-tune is more concise — ask for "3 tips" and it gives exactly 3. Base writes a 1,200-character essay. ✅ Pure native Hindi — base keeps slipping into English ("संतुलित आहार (Eat a Balanced Diet)", "तारा (Star)"). My fine-tune stays in clean Hindi. ✅ Tighter instruction-following — ask for a "short message" and it gives one, not a menu of options. ⚖️ And to be honest: base Gemma-4 is more detailed and comprehensive. I didn't build a "smarter" model — I built a focused, Hindi-native, edge-friendly one that runs as a 5GB GGUF (Q4) on CPU. 🔗 Try it: Live demo (CPU): https://huggingface.co/spaces/pankajpandey-dev/gemma-4-e4b-hindi-demo GGUF (Ollama/llama.cpp): https://huggingface.co/pankajpandey-dev/gemma-4-e4b-hindi-instruct-GGUF 16-bit model: https://huggingface.co/pankajpandey-dev/gemma-4-e4b-hindi-instruct Built with @unsloth · Data by @ai4bharat 🙏 #Hindi #LLM #Gemma #Unsloth #IndicNLP #GGUF
reacted to theirpost with 👀 about 4 hours ago
🇮🇳 New in my Hindi LLM Series: Gemma-4 E4B, fine-tuned for Hindi — and it runs on your laptop's CPU. I fine-tuned Google's new Gemma-4 E4B on ~10k Hindi instruction pairs (AI4Bharat: anudesh + dolly) using Unsloth + LoRA, on a single L4 GPU. Then I ran an honest side-by-side eval: base Gemma-4 vs my fine-tune, across 25 Hindi prompts. The results were interesting 👇 ✅ My fine-tune is more concise — ask for "3 tips" and it gives exactly 3. Base writes a 1,200-character essay. ✅ Pure native Hindi — base keeps slipping into English ("संतुलित आहार (Eat a Balanced Diet)", "तारा (Star)"). My fine-tune stays in clean Hindi. ✅ Tighter instruction-following — ask for a "short message" and it gives one, not a menu of options. ⚖️ And to be honest: base Gemma-4 is more detailed and comprehensive. I didn't build a "smarter" model — I built a focused, Hindi-native, edge-friendly one that runs as a 5GB GGUF (Q4) on CPU. 🔗 Try it: Live demo (CPU): https://huggingface.co/spaces/pankajpandey-dev/gemma-4-e4b-hindi-demo GGUF (Ollama/llama.cpp): https://huggingface.co/pankajpandey-dev/gemma-4-e4b-hindi-instruct-GGUF 16-bit model: https://huggingface.co/pankajpandey-dev/gemma-4-e4b-hindi-instruct Built with @unsloth · Data by @ai4bharat 🙏 #Hindi #LLM #Gemma #Unsloth #IndicNLP #GGUF
updated a model about 11 hours ago
pankajpandey-dev/gemma-4-e4b-hindi-instruct-GGUF
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