Instructions to use Ila-AI/IlaAI-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Ila-AI/IlaAI-v3 with MLX:

# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("Ila-AI/IlaAI-v3")

prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True
)

text = generate(model, tokenizer, prompt=prompt, verbose=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use Ila-AI/IlaAI-v3 with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "Ila-AI/IlaAI-v3"

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Ila-AI/IlaAI-v3"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use Ila-AI/IlaAI-v3 with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "Ila-AI/IlaAI-v3"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "Ila-AI/IlaAI-v3"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "Ila-AI/IlaAI-v3",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use Ila-AI/IlaAI-v3 with Hermes Agent:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "Ila-AI/IlaAI-v3"

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default Ila-AI/IlaAI-v3

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Ila-AI/IlaAI-v3 with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "Ila-AI/IlaAI-v3"

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "Ila-AI/IlaAI-v3" \
  --custom-provider-id mlx-lm \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

IlaAI-v3 / README.md

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---
language:
- en
- hi
- te
license: apache-2.0
library_name: mlx
tags:
- agriculture
- indian-farming
- fine-tuned
- lora
- qwen3
- mlx
- crops
- farming
- india
- kcc
- kisan-call-center
base_model: Ila-AI/IlaAI-v1.1
datasets:
- KissanAI/Thinking-climate-100k
- daskoushik/farmers-call-query-data-qa
pipeline_tag: text-generation
---
<div align="center">

<img src="https://cdn-avatars.huggingface.co/v1/production/uploads/67a527986b39b58ea8528fb0/i_tvZOmu3un4ABR8Z0Fyp.png" alt="IlaAI Logo" width="120"/>

# IlaAI-v3 🌱
### Earth · Crop · Intelligence

**An open-source Agricultural AI for Bharat's Farmers**

[![HuggingFace](https://img.shields.io/badge/HuggingFace-Ila--AI-yellow?logo=huggingface)](https://huggingface.co/Ila-AI)
[![GitHub](https://img.shields.io/badge/GitHub-IlaAI-green?logo=github)](https://github.com/IlaAI)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue)](LICENSE)
[![Val Loss](https://img.shields.io/badge/Val%20Loss-0.598-brightgreen)]()

</div>

---

## 🌾 What is IlaAI?

**IlaAI** (इला — Sanskrit for *"the earth that gives"*) is an open-source LLM series built specifically for Indian agriculture. Our mission is simple — give every farmer in India access to expert agricultural advice, for free, in their own language.

> "For the hands that feed a billion 🌾"

---

## 🏆 What's New in v3?

IlaAI-v3 is our biggest leap yet — trained on **real farmer data** from India's Kisan Call Center (KCC).

- 🏆 **Best val loss ever — 0.598**
- 🌾 **175,000+ real farmer Q&A pairs** from KCC
- 🗣️ **Telugu support** (experimental)
- ⚡ **Fast responses** with `enable_thinking=False`
- 🇮🇳 **India-specific** — real crops, real problems, real solutions


## 📊 How v3 Compares

| Feature | v1 | v1.1 | v3 |
|---------|-----|------|-----|
| Dataset | Synthetic 96K | Thinking 100K | **Real KCC 175K** |
| Val Loss | 0.695 | 0.821 | **0.598** |
| English | ✅ Good | ✅ Better | ✅ Excellent |
| Hindi | ❌ Weak | ⚠️ Basic | ✅ Good |
| Telugu | ❌ None | ❌ None | ⚠️ Experimental |
| Real Farmer Data | ❌ | ❌ | ✅ |
| Thinking Disabled | ❌ | ❌ | ✅ |
| Response Speed | Slow | Slow | **Fast** |

---

## 🌾 About the KCC Dataset

The **Kisan Call Center (KCC)** is a Government of India initiative launched in 2004. Farmers across India call a toll-free number (1800-180-1551) to get expert advice on agriculture. Every call is logged — the farmer's question and the expert's answer.

This dataset contains **175,000+ real farmer questions** with expert answers, covering:
- Crop diseases and pest management
- Fertilizer and pesticide recommendations
- Irrigation and water management
- Government schemes and subsidies
- Market prices and crop selection
- Region-specific advice across all Indian states

Training on this data means IlaAI speaks like a real agricultural expert — because it learned from real agricultural experts. 🌱

---

## 🚀 Quick Start

```python
from mlx_lm import load, generate
from mlx_lm.sample_utils import make_sampler
model, tokenizer = load("Ila-AI/IlaAI-v3")
messages = [
    {"role": "system", "content": "You are IlaAI, an expert agricultural assistant for Indian farmers. Always respond in the same language the user writes in. Be concise, practical and helpful."},
    {"role": "user", "content": "My wheat crop has yellow spots on leaves. What should I do?"}
]
text = tokenizer.apply_chat_template(
    messages,
    add_generation_prompt=True,
    tokenize=False,
    enable_thinking=False  # Always add this for fast responses!
)
sampler = make_sampler(temp=0.3, top_p=0.9)
response = generate(model, tokenizer, prompt=text, max_tokens=500, sampler=sampler, verbose=True)
```

---

## ⚡ Important — Always Disable Thinking Mode

```python
text = tokenizer.apply_chat_template(
    messages,
    add_generation_prompt=True,
    tokenize=False,
    enable_thinking=False  # Critical! Always add this.
)
```

Without `enable_thinking=False`, the model wastes tokens on internal reasoning and responses are slower and lower quality.

---

## 📊 Training Details

| Detail | Value |
|--------|-------|
| Base Model | IlaAI-v1.1 (Qwen3-4B) |
| Framework | MLX LoRA |
| Hardware | Apple M4 Mac Mini (24GB) |
| Dataset 1 | KCC 175K real farmer Q&A |
| Dataset 2 | KissanAI Thinking-climate-100k |
| Dataset 3 | 1,515 Telugu Q&A pairs |
| Training iters | 3,000 |
| LoRA rank | 8 |
| Final Val Loss | **0.598** |
| Peak Memory | 8.3 GB |

---

## 🗣️ Language Support

| Language | Status |
|----------|--------|
| English | ✅ Excellent |
| Hindi | ✅ Good |
| Telugu | ⚠️ Experimental |
| Tamil | 🔄 Coming in v4 |
| Kannada | 🔄 Coming in v4 |
| Marathi | 🔄 Coming in v4 |
| Bengali | 🔄 Coming in v4 |
| Gujarati | 🔄 Coming in v4 |
| Punjabi | 🔄 Coming in v4 |

---

## 📈 Model Evolution

| Version | Dataset | Val Loss | Status |
|---------|---------|----------|--------|
| v1 | KissanAI 96K synthetic | 0.695 | ✅ Released |
| v1.1 | KissanAI 100K thinking | 0.821 | ✅ Released |
| v3 | KCC 175K real + Telugu | **0.598** | ✅ Released |
| v4 | Full 22+ Indian languages | TBD | 🔄 Coming |

---

## 🗺️ Complete Roadmap

### ✅ Phase 1 — Foundation (Done)
- [x] IlaAI-v1 — English agriculture advisory (96K synthetic rows)
- [x] IlaAI-v1.1 — Improved English (100K thinking dataset)
- [x] IlaAI-v3 — KCC real farmer data + Telugu experimental

### 🔄 Phase 2 — True Multilingual (v4)
- [ ] 22+ Indian languages with proper quality
- [ ] Real multilingual agriculture Q&A
- [ ] BPCC + AI4Bharat datasets
- [ ] Release IlaAI-v4

### 👁️ Phase 3 — Vision (IlaAI-Vision)
- [ ] Crop disease detection from photos
- [ ] Support all major Indian crops
- [ ] Combine text + vision into one model

### 📱 Phase 4 — Mobile App (Free Forever)
- [ ] Free Android app
- [ ] Free iOS app
- [ ] On-device inference (no internet needed)
- [ ] Voice input in Indian languages
- [ ] Available on Play Store & App Store

### 🌍 Phase 5 — Global
- [ ] Expand beyond India
- [ ] Support farmers worldwide — Africa, Southeast Asia, South America
- [ ] Open API for developers
- [ ] WhatsApp bot integration

---

## 🤝 Contributing

We welcome contributions from developers, farmers, agronomists, and language experts!

- 📂 Add regional crop data
- 🌐 Help with Indian language translations
- 🐛 Report issues
- 💡 Suggest features

---

## 📜 License

Apache 2.0 — free to use, fine-tune, and build upon.

---

## 🙏 Acknowledgements

- [KissanAI](https://huggingface.co/KissanAI) for open-sourcing Dhenu models and datasets
- [Kisan Call Center](https://data.gov.in) — Government of India
- [Qwen Team](https://huggingface.co/Qwen) for Qwen3 base models
- [Apple MLX Team](https://github.com/ml-explore/mlx) for MLX framework
- Every Indian farmer who inspired this project 🌾

---

<div align="center">
  <b>For the hands that feed a billion 🌾</b><br/>
  <a href="https://huggingface.co/Ila-AI">HuggingFace</a> · <a href="https://github.com/IlaAI">GitHub</a>
</div>

	---
	language:
	- en
	- hi
	- te
	license: apache-2.0
	library_name: mlx
	tags:
	- agriculture
	- indian-farming
	- fine-tuned
	- lora
	- qwen3
	- mlx
	- crops
	- farming
	- india
	- kcc
	- kisan-call-center
	base_model: Ila-AI/IlaAI-v1.1
	datasets:
	- KissanAI/Thinking-climate-100k
	- daskoushik/farmers-call-query-data-qa
	pipeline_tag: text-generation
	---

	<div align="center">

	<img src="https://cdn-avatars.huggingface.co/v1/production/uploads/67a527986b39b58ea8528fb0/i_tvZOmu3un4ABR8Z0Fyp.png" alt="IlaAI Logo" width="120"/>

	# IlaAI-v3 🌱
	### Earth · Crop · Intelligence

	An open-source Agricultural AI for Bharat's Farmers

	[![HuggingFace](https://img.shields.io/badge/HuggingFace-Ila--AI-yellow?logo=huggingface)](https://huggingface.co/Ila-AI)
	[![GitHub](https://img.shields.io/badge/GitHub-IlaAI-green?logo=github)](https://github.com/IlaAI)
	[![License](https://img.shields.io/badge/License-Apache%202.0-blue)](LICENSE)
	[![Val Loss](https://img.shields.io/badge/Val%20Loss-0.598-brightgreen)]()

	</div>

	---

	## 🌾 What is IlaAI?

	IlaAI (इला — Sanskrit for "the earth that gives") is an open-source LLM series built specifically for Indian agriculture. Our mission is simple — give every farmer in India access to expert agricultural advice, for free, in their own language.

	> "For the hands that feed a billion 🌾"

	---

	## 🏆 What's New in v3?

	IlaAI-v3 is our biggest leap yet — trained on real farmer data from India's Kisan Call Center (KCC).

	- 🏆 Best val loss ever — 0.598
	- 🌾 175,000+ real farmer Q&A pairs from KCC
	- 🗣️ Telugu support (experimental)
	- ⚡ Fast responses with `enable_thinking=False`
	- 🇮🇳 India-specific — real crops, real problems, real solutions


	## 📊 How v3 Compares

	\| Feature \| v1 \| v1.1 \| v3 \|
	\|---------\|-----\|------\|-----\|
	\| Dataset \| Synthetic 96K \| Thinking 100K \| Real KCC 175K \|
	\| Val Loss \| 0.695 \| 0.821 \| 0.598 \|
	\| English \| ✅ Good \| ✅ Better \| ✅ Excellent \|
	\| Hindi \| ❌ Weak \| ⚠️ Basic \| ✅ Good \|
	\| Telugu \| ❌ None \| ❌ None \| ⚠️ Experimental \|
	\| Real Farmer Data \| ❌ \| ❌ \| ✅ \|
	\| Thinking Disabled \| ❌ \| ❌ \| ✅ \|
	\| Response Speed \| Slow \| Slow \| Fast \|

	---

	## 🌾 About the KCC Dataset

	The Kisan Call Center (KCC) is a Government of India initiative launched in 2004. Farmers across India call a toll-free number (1800-180-1551) to get expert advice on agriculture. Every call is logged — the farmer's question and the expert's answer.

	This dataset contains 175,000+ real farmer questions with expert answers, covering:
	- Crop diseases and pest management
	- Fertilizer and pesticide recommendations
	- Irrigation and water management
	- Government schemes and subsidies
	- Market prices and crop selection
	- Region-specific advice across all Indian states

	Training on this data means IlaAI speaks like a real agricultural expert — because it learned from real agricultural experts. 🌱

	---

	## 🚀 Quick Start

	```python
	from mlx_lm import load, generate
	from mlx_lm.sample_utils import make_sampler

	model, tokenizer = load("Ila-AI/IlaAI-v3")

	messages = [
	{"role": "system", "content": "You are IlaAI, an expert agricultural assistant for Indian farmers. Always respond in the same language the user writes in. Be concise, practical and helpful."},
	{"role": "user", "content": "My wheat crop has yellow spots on leaves. What should I do?"}
	]

	text = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=False,
	enable_thinking=False # Always add this for fast responses!
	)

	sampler = make_sampler(temp=0.3, top_p=0.9)
	response = generate(model, tokenizer, prompt=text, max_tokens=500, sampler=sampler, verbose=True)
	```

	---

	## ⚡ Important — Always Disable Thinking Mode

	```python
	text = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=False,
	enable_thinking=False # Critical! Always add this.
	)
	```

	Without `enable_thinking=False`, the model wastes tokens on internal reasoning and responses are slower and lower quality.

	---

	## 📊 Training Details

	\| Detail \| Value \|
	\|--------\|-------\|
	\| Base Model \| IlaAI-v1.1 (Qwen3-4B) \|
	\| Framework \| MLX LoRA \|
	\| Hardware \| Apple M4 Mac Mini (24GB) \|
	\| Dataset 1 \| KCC 175K real farmer Q&A \|
	\| Dataset 2 \| KissanAI Thinking-climate-100k \|
	\| Dataset 3 \| 1,515 Telugu Q&A pairs \|
	\| Training iters \| 3,000 \|
	\| LoRA rank \| 8 \|
	\| Final Val Loss \| 0.598 \|
	\| Peak Memory \| 8.3 GB \|

	---

	## 🗣️ Language Support

	\| Language \| Status \|
	\|----------\|--------\|
	\| English \| ✅ Excellent \|
	\| Hindi \| ✅ Good \|
	\| Telugu \| ⚠️ Experimental \|
	\| Tamil \| 🔄 Coming in v4 \|
	\| Kannada \| 🔄 Coming in v4 \|
	\| Marathi \| 🔄 Coming in v4 \|
	\| Bengali \| 🔄 Coming in v4 \|
	\| Gujarati \| 🔄 Coming in v4 \|
	\| Punjabi \| 🔄 Coming in v4 \|

	---

	## 📈 Model Evolution

	\| Version \| Dataset \| Val Loss \| Status \|
	\|---------\|---------\|----------\|--------\|
	\| v1 \| KissanAI 96K synthetic \| 0.695 \| ✅ Released \|
	\| v1.1 \| KissanAI 100K thinking \| 0.821 \| ✅ Released \|
	\| v3 \| KCC 175K real + Telugu \| 0.598 \| ✅ Released \|
	\| v4 \| Full 22+ Indian languages \| TBD \| 🔄 Coming \|

	---

	## 🗺️ Complete Roadmap

	### ✅ Phase 1 — Foundation (Done)
	- [x] IlaAI-v1 — English agriculture advisory (96K synthetic rows)
	- [x] IlaAI-v1.1 — Improved English (100K thinking dataset)
	- [x] IlaAI-v3 — KCC real farmer data + Telugu experimental

	### 🔄 Phase 2 — True Multilingual (v4)
	- [ ] 22+ Indian languages with proper quality
	- [ ] Real multilingual agriculture Q&A
	- [ ] BPCC + AI4Bharat datasets
	- [ ] Release IlaAI-v4

	### 👁️ Phase 3 — Vision (IlaAI-Vision)
	- [ ] Crop disease detection from photos
	- [ ] Support all major Indian crops
	- [ ] Combine text + vision into one model

	### 📱 Phase 4 — Mobile App (Free Forever)
	- [ ] Free Android app
	- [ ] Free iOS app
	- [ ] On-device inference (no internet needed)
	- [ ] Voice input in Indian languages
	- [ ] Available on Play Store & App Store

	### 🌍 Phase 5 — Global
	- [ ] Expand beyond India
	- [ ] Support farmers worldwide — Africa, Southeast Asia, South America
	- [ ] Open API for developers
	- [ ] WhatsApp bot integration

	---

	## 🤝 Contributing

	We welcome contributions from developers, farmers, agronomists, and language experts!

	- 📂 Add regional crop data
	- 🌐 Help with Indian language translations
	- 🐛 Report issues
	- 💡 Suggest features

	---

	## 📜 License

	Apache 2.0 — free to use, fine-tune, and build upon.

	---

	## 🙏 Acknowledgements

	- [KissanAI](https://huggingface.co/KissanAI) for open-sourcing Dhenu models and datasets
	- [Kisan Call Center](https://data.gov.in) — Government of India
	- [Qwen Team](https://huggingface.co/Qwen) for Qwen3 base models
	- [Apple MLX Team](https://github.com/ml-explore/mlx) for MLX framework
	- Every Indian farmer who inspired this project 🌾

	---

	<div align="center">
	<b>For the hands that feed a billion 🌾</b><br/>
	<a href="https://huggingface.co/Ila-AI">HuggingFace</a> · <a href="https://github.com/IlaAI">GitHub</a>
	</div>