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README.md

@@ -1,21 +1,101 @@
 ---
-base_model: unsloth/gemma-4-e4b-it-unsloth-bnb-4bit
-tags:
-- text-generation-inference
-- transformers
-- unsloth
-- gemma4
-license: apache-2.0
+license: gemma
+base_model: unsloth/gemma-4-E4B-it
 language:
+- hi
 - en
+tags:
+- hindi
+- indic
+- gemma
+- unsloth
+- text-generation
+datasets:
+- ai4bharat/indic-instruct-data-v0.1
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+# 🇮🇳 Gemma-4-E4B-Hindi-Instruct (16-bit)
+
+A Hindi instruction-tuned fine-tune of **Gemma 4 E4B**. This is the merged 16-bit model for use with 🤗 Transformers / vLLM / further fine-tuning.
+
+For local CPU/edge use, see the **GGUF** build.
+
+> Part of my **Hindi LLM Series** — small, openly-documented Indic models that actually follow instructions in Hindi and run on your own machine.
+
+---
+
+## Usage (Transformers)
+
+```python
+from transformers import AutoModelForCausalLM, AutoProcessor
+import torch
+
+model_id = "pankajpandey-dev/gemma-4-e4b-hindi-instruct"
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto")
+proc  = AutoProcessor.from_pretrained(model_id)
+
+msgs = [{"role": "user", "content": [{"type": "text", "text": "मशीन लर्निंग को आसान शब्दों में समझाओ।"}]}]
+inputs = proc.apply_chat_template(msgs, add_generation_prompt=True, tokenize=True,
+                                  return_dict=True, return_tensors="pt").to(model.device)
+out = model.generate(**inputs, max_new_tokens=256, use_cache=True)
+print(proc.decode(out[0], skip_special_tokens=True))
+```
+
+---
+
+## Example outputs
+
+**Prompt:** भारत के बारे में एक रोचक तथ्य बताओ।
+> भारत दुनिया में सबसे अधिक भाषाओं वाले देशों में से एक है — 22 आधिकारिक भाषाएँ और 1,000 से अधिक बोलियाँ। हिंदी एक इंडो-आर्यन भाषा है, जबकि तमिल एक द्रविड़ भाषा है।
+
+---
+
+## Training details
+
+| | |
+|---|---|
+| Base model | `unsloth/gemma-4-E4B-it` |
+| Method | LoRA (r=16, α=16), response-only loss |
+| Framework | [Unsloth](https://github.com/unslothai/unsloth) |
+| Data | ~10k Hindi instruction pairs (AI4Bharat indic-instruct: anudesh + dolly, hi splits) |
+| Epochs | 2 |
+| LR / schedule | 1e-4, cosine |
+| Precision | bf16 (4-bit QLoRA base) |
+| Hardware | Single NVIDIA L4 (24 GB) |
+| Final train loss | ~0.29 |
+
+Trained text-only (vision layers frozen), single-BOS chat template to avoid double-BOS corruption.
+
+---
+
+## Related repos
+
+- GGUF (Q4/Q5/Q8): [`pankajpandey-dev/gemma-4-e4b-hindi-instruct-GGUF`](https://huggingface.co/pankajpandey-dev/gemma-4-e4b-hindi-instruct-GGUF)
+- LoRA adapter: [`pankajpandey-dev/gemma-4-e4b-hindi-instruct-lora`](https://huggingface.co/pankajpandey-dev/gemma-4-e4b-hindi-instruct-lora)
+
+---
+
+## Provenance & license (please read)
+
+Mixed-license lineage — review all before redistribution or commercial use:
+
+- **Weights** derive from **Gemma 4**, under the [Gemma Terms of Use](https://ai.google.dev/gemma/terms).
+- **Data** from [AI4Bharat indic-instruct-data-v0.1](https://huggingface.co/datasets/ai4bharat/indic-instruct-data-v0.1):
+  - **Dolly** split — from `databricks-dolly-15k`, **CC-BY-SA-3.0**.
+  - **Anudesh** split — responses from **Llama-2-70B**, so the **Llama 2 Community License** applies.
+
+Raw training data is not redistributed here. You are responsible for complying with the Gemma, Llama 2, and CC-BY-SA terms.
+
 ---
 
-# Uploaded finetuned  model
+## Limitations
 
-- **Developed by:** pankajpandey-dev
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/gemma-4-e4b-it-unsloth-bnb-4bit
+- ~8B-class model: strong Hindi fluency, but can hallucinate facts and occasionally repeat phrasing on long open-ended generation.
+- Tuned for single-turn Hindi instructions; long multi-turn chat is not the focus.
+- Not safety-aligned for production.
 
-This gemma4 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+## Acknowledgements
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+Base model by Google (Gemma 4). Data by AI4Bharat. Fine-tuning with Unsloth. 🙏