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Model: pankajpandey-dev/Qwen3-0.6B-Hindi-Instruct-v1-GGUF Source: Original Platform
2026-06-10 11:26:17 +08:00
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+---
+language:
+- hi
+- en
+license: apache-2.0
+tags:
+- fine-tuned
+- gguf
+- hindi
+- india
+- instruction-tuned
+- llama.cpp
+- ollama
+- quantized
+- qwen3
+base_model: pankajpandey-dev/Qwen3-0.6B-Hindi-Instruct-v1
+pipeline_tag: text-generation
+base_model_relation: quantized
+---
+> ⚠️ **Note:** This 0.6B version is undertrained and does not reliably follow Hindi instructions. For a working Hindi model, please use **[Qwen3-4B-Hindi-Instruct-v2](https://huggingface.co/pankajpandey-dev/Qwen3-4B-Hindi-Instruct-v2)** ([GGUF here](https://huggingface.co/pankajpandey-dev/Qwen3-4B-Hindi-Instruct-v2-GGUF)).
+
+---
+
+
+# Qwen3-0.6B Hindi Instruct v1 — GGUF
+
+The smallest Hindi-capable instruction model you can run locally — fits in 370MB, runs on any laptop, no GPU needed.
+
+Fine-tuned from Qwen/Qwen3-0.6B on English to Hindi instruction pairs.
+Quantized to GGUF for local inference with llama.cpp, LM Studio, and Ollama.
+
+---
+
+## Quick Start
+
+Download the model using huggingface-cli:
+
+    huggingface-cli download pankajpandey-dev/Qwen3-0.6B-Hindi-Instruct-v1-GGUF Qwen3-0.6B-Hindi-v1-Q4_K_M.gguf --local-dir .
+
+Run with llama.cpp:
+
+    ./llama-cli -m Qwen3-0.6B-Hindi-v1-Q4_K_M.gguf -p "भारत की राजधानी क्या है?" -n 256
+
+Or open directly in LM Studio — New Model — Search pankajpandey-dev
+
+---
+
+## Available Versions
+
+| File | Quantization | Size | RAM Needed | Best For |
+|------|-------------|------|-----------|---------|
+| Qwen3-0.6B-Hindi-v1-Q2_K.gguf | Q2_K | 0.28 GB | 1 GB | Minimum hardware |
+| Qwen3-0.6B-Hindi-v1-Q4_K_M.gguf | Q4_K_M | 0.37 GB | 1.5 GB | Recommended |
+| Qwen3-0.6B-Hindi-v1-Q5_K_M.gguf | Q5_K_M | 0.41 GB | 2 GB | Better quality |
+| Qwen3-0.6B-Hindi-v1-Q8_0.gguf | Q8_0 | 0.60 GB | 2.5 GB | Highest quality |
+
+Not sure which to pick? Always start with Q4_K_M — best balance of speed, size, and quality.
+
+---
+
+## Model Details
+
+| Property | Value |
+|----------|-------|
+| Base Model | Qwen/Qwen3-0.6B |
+| Parameters | 600M |
+| Architecture | Qwen2 — fully supported by llama.cpp |
+| Fine-tune Method | QLoRA with LoRA r=16 alpha=16 |
+| Training Steps | 60 steps |
+| Training Data | 2000 English to Hindi instruction pairs |
+| Max Context | 2048 tokens |
+| Languages | Hindi and English |
+| License | Apache 2.0 — commercial use allowed |
+
+---
+
+## Example Prompts
+
+Hindi Question Answering:
+
+    User: भारत की राजधानी क्या है?
+    Model: भारत की राजधानी नई दिल्ली है।
+
+Hindi Instructions:
+
+    User: मुझे चाय बनाने का तरीका बताओ।
+    Model: चाय बनाने के लिए पहले पानी गरम करें...
+
+Mixed Language:
+
+    User: Python में for loop कैसे लिखते हैं?
+    Model: Python में for loop इस तरह लिखते हैं...
+
+---
+
+## Compatibility
+
+| Tool | Status |
+|------|--------|
+| llama.cpp | Full support |
+| LM Studio | Full support |
+| Ollama | Full support |
+| Jan | Full support |
+| Open WebUI | Full support |
+
+---
+
+## Recommended Settings
+
+    Temperature:    0.7
+    Top-P:          0.9
+    Top-K:          40
+    Repeat Penalty: 1.1
+    Context Length: 2048
+
+---
+
+## Why This Model?
+
+- Tiny — 370MB, one of the smallest Hindi-capable GGUF models available
+- Fast — runs fully on CPU, no GPU required
+- Hindi-first — specifically trained for Hindi instruction following
+- Open — Apache 2.0, free for personal and commercial use
+- Actively maintained — v2 coming soon with more data
+
+---
+
+## Roadmap
+
+- Done: v1 — Base Hindi fine-tune on Qwen3-0.6B
+- Next: v2 — 10x larger dataset, improved Hindi fluency
+- Next: v3 — better instruction following
+- Next: Qwen3-1.7B-Hindi — bigger model, same niche
+- Next: Live demo Space on HuggingFace
+
+---
+
+## Related Repos
+
+| Repo | Description |
+|------|-------------|
+| pankajpandey-dev/Qwen3-0.6B-Hindi-Instruct-v1 | Full precision model in safetensors format |
+| pankajpandey-dev/Qwen3-0.6B-Hindi-Instruct-v1-GGUF | This repo — GGUF quantized versions |
+
+---
+
+## About the Author
+
+Made by pankajpandey-dev
+Building open-source Hindi AI models for India
+
+Follow for weekly model updates and new Hindi LLM releases.
+
+Found this useful? Please like this repo — it helps other Hindi speakers find it.