Instructions to use Ila-AI/IlaAI-v1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Ila-AI/IlaAI-v1.1 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-v1.1")

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-v1.1 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-v1.1"

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/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-v1.1"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use Ila-AI/IlaAI-v1.1 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-v1.1"

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-v1.1

Run Hermes

hermes

OpenClaw new

How to use Ila-AI/IlaAI-v1.1 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-v1.1"

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-v1.1" \
  --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"

MLX LM

How to use Ila-AI/IlaAI-v1.1 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-v1.1"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "Ila-AI/IlaAI-v1.1"
# 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-v1.1",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

IlaAI-v1.1 / README.md

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	---
	language:
	- en
	- hi
	- te
	- ta
	- kn
	- mr
	- bn
	- gu
	- pa
	license: apache-2.0
	library_name: mlx
	tags:
	- agriculture
	- indian-farming
	- fine-tuned
	- lora
	- qwen3
	- mlx
	- crops
	- farming
	- india
	base_model: Ila-AI/IlaAI-v1
	datasets:
	- KissanAI/Thinking-climate-100k
	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-v1.1 🌱
	### 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)
	[![Base Model](https://img.shields.io/badge/Base-IlaAI--v1-purple)]()
	[![Val Loss](https://img.shields.io/badge/Val%20Loss-0.821-brightgreen)]()

	</div>

	---

	## 🌾 What's New in v1.1?

	IlaAI-v1.1 is an improved version of IlaAI-v1 with:

	- 5x more training data — 9,000 rows vs 1,800 rows
	- Better dataset — KissanAI Thinking-climate-100k (chain-of-thought reasoning)
	- More training — 3,000 iterations vs 2,000 iterations
	- Better Val Loss — 0.821 vs 0.874
	- Multilingual system prompt — responds in user's language

	---

	## 🚀 Quick Start

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

	model, tokenizer = load("Ila-AI/IlaAI-v1.1")

	messages = [
	{"role": "system", "content": "You are IlaAI, an expert agricultural assistant for Indian farmers. Always respond in the same language the user writes in. Keep answers concise, practical and under 200 words."},
	{"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
	)

	sampler = make_sampler(temp=0.7, top_p=0.9)
	response = generate(model, tokenizer, prompt=text, max_tokens=1000, sampler=sampler, verbose=True)
	```

	---

	## 📊 Training Details

	\| Detail \| Value \|
	\|--------\|-------\|
	\| Base Model \| IlaAI-v1 (Qwen3-4B) \|
	\| Framework \| MLX LoRA \|
	\| Hardware \| Apple M4 Mac Mini (24GB) \|
	\| Dataset \| KissanAI/Thinking-climate-100k \|
	\| Training rows \| 9,000 \|
	\| Validation rows \| 1,000 \|
	\| Training iters \| 3,000 \|
	\| LoRA rank \| 8 \|
	\| Final Val Loss \| 0.821 \|
	\| Peak Memory \| 4.507 GB \|

	---

	## 🗣️ Language Support

	\| Language \| Status \|
	\|----------\|--------\|
	\| English \| ✅ Excellent \|
	\| Hindi \| ✅ Good \|
	\| Telugu \| ⚠️ Basic \|
	\| Tamil \| ⚠️ Basic \|
	\| Kannada \| ⚠️ Basic \|
	\| Others \| ⚠️ Basic \|

	> Full multilingual support coming in IlaAI-v2 with real multilingual agriculture data.

	---

	## ⚠️ Limitations

	- Best performance in English — primary training language
	- Hindi — good quality responses
	- Other Indian languages — basic support, improving in v2
	- Text only — vision model coming separately

	---

	## 🗺️ Roadmap

	### ✅ Phase 1 — Foundation
	- [x] IlaAI-v1 — English agriculture advisory
	- [x] IlaAI-v1.1 — Improved English + basic multilingual

	### 🔄 Phase 2 — True Multilingual (v2)
	- [ ] Real multilingual agriculture data (BPCC + AI4Bharat)
	- [ ] 22+ Indian languages with proper quality
	- [ ] Release IlaAI-v2

	### 👁️ Phase 3 — Vision
	- [ ] Crop disease detection from photos
	- [ ] IlaAI-Vision model

	### 📱 Phase 4 — Mobile App
	- [ ] Free Android & iOS app
	- [ ] On-device inference
	- [ ] Voice input in Indian languages

	### 🌍 Phase 5 — Global
	- [ ] Expand beyond India
	- [ ] Support farmers worldwide
	- [ ] API for developers

	---

	## 📜 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
	- [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>