Instructions to use Anoopsingh53/isro-spaceai-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Anoopsingh53/isro-spaceai-v1 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Anoopsingh53/isro-spaceai-v1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Anoopsingh53/isro-spaceai-v1")
model = AutoModelForCausalLM.from_pretrained("Anoopsingh53/isro-spaceai-v1", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Anoopsingh53/isro-spaceai-v1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Anoopsingh53/isro-spaceai-v1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Anoopsingh53/isro-spaceai-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Anoopsingh53/isro-spaceai-v1

SGLang

How to use Anoopsingh53/isro-spaceai-v1 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Anoopsingh53/isro-spaceai-v1" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Anoopsingh53/isro-spaceai-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Anoopsingh53/isro-spaceai-v1" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Anoopsingh53/isro-spaceai-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Anoopsingh53/isro-spaceai-v1 with Docker Model Runner:
```
docker model run hf.co/Anoopsingh53/isro-spaceai-v1
```

Anoopsingh53 commited on about 23 hours ago

Commit

401e96e

verified ·

1 Parent(s): be90ceb

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@@ -1,26 +1,42 @@
 ---
 language:
 - en
 license: apache-2.0
 base_model: Qwen/Qwen2.5-7B-Instruct
 tags:
 - space
-- astrophysics
-- heliophysics
-- oceanography
-- remote-sensing
-- sar-radar
 - isro
 - aditya-l1
 - chandrayaan-3
 - oceansat-3
 - calcofi
 - sentinel-1
-- nasa-kepler
-- graphrag
-- rig
 - sonification
-- enterprise
 datasets:
 - UniverseTBD/arxiv-qa-astro-ph
 - Anoopsingh53/isro-space-ocean-dataset
@@ -58,8 +74,8 @@ model-index:
 <div align="center">
-# 🛰️ SpaceAI-v1.1 (7B Foundation Model)
-### **An Enterprise-Grade Multimodal Foundation Model for Heliophysics, Oceanography, and Planetary Observation**
 [![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
 [![Base Model](https://img.shields.io/badge/Base_Architecture-Qwen_2.5_7B_Instruct-792ee5.svg)](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)
@@ -74,11 +90,20 @@ model-index:
 ---
-## Executive Summary
-**SpaceAI-v1.1** is a domain-specialized 7-Billion parameter foundation language model engineered for mission-critical scientific reasoning across **Solar Heliophysics, Earth Observation, Marine Oceanography, and Deep Exoplanetary Science**.
-Trained through **QLoRA parameter-efficient fine-tuning with full FP16 weight safe-merging**, SpaceAI bridges multi-scale scientific disciplines—from sub-nanometer solar EUV spectral flux ($130 - 285\text{ nm}$) captured by **ISRO Aditya-L1** to deep-sea CTD hydrographic profiles from **CalCOFI** and light-curve transit photometry from **NASA Kepler**.
 ---

 ---
 language:
 - en
+- hi
 license: apache-2.0
 base_model: Qwen/Qwen2.5-7B-Instruct
 tags:
 - space
 - isro
+- nasa
 - aditya-l1
+- chandrayaan
 - chandrayaan-3
+- astrophysics
+- astronomy
+- cosmology
+- oceansat
 - oceansat-3
 - calcofi
+- oceanography
 - sentinel-1
+- sar
+- radar
+- flood
+- remote-sensing
+- earth-observation
+- kepler
+- exoplanet
+- space-weather
+- solar-flare
+- suit
+- heliophysics
+- multimodal
 - sonification
+- qlora
+- fp16
+- text-generation
+- national-space-day
+- india
 datasets:
 - UniverseTBD/arxiv-qa-astro-ph
 - Anoopsingh53/isro-space-ocean-dataset
 <div align="center">
+# 🛰️ SpaceAI-v1.1: ISRO & NASA 7B Multi-Domain Foundation Model
+### **India's First Unified Foundation Intelligence for Space Exploration, Heliophysics, Oceanography & Earth Observation**
 [![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
 [![Base Model](https://img.shields.io/badge/Base_Architecture-Qwen_2.5_7B_Instruct-792ee5.svg)](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)
 ---
+## Executive Summary & Overview
+**SpaceAI-v1.1** (`Anoopsingh53/isro-spaceai-v1`) is an open-weights, domain-specialized 7-Billion parameter foundation language model purpose-built for scientific reasoning in **ISRO Space Missions, Heliophysics, Solar Flares, NASA Kepler Exoplanets, CalCOFI Marine Oceanography, and Sentinel-1 SAR Flood Remote Sensing**.
+Trained through **QLoRA parameter-efficient fine-tuning with full FP16 weight safe-merging**, SpaceAI bridges multi-scale scientific disciplines—from sub-nanometer solar EUV spectral flux ($130 - 285\text{ nm}$) captured by **ISRO Aditya-L1 (SUIT / PAPA / VELC)** to deep-sea CTD hydrographic profiles from **CalCOFI / Oceansat-3** and light-curve transit photometry from **NASA Kepler**.
+---
+## Keywords & Search Indexing (SEO)
+- **ISRO Missions:** Aditya-L1, Chandrayaan-3, Oceansat-3, AstroSat, Gaganyaan, MOSDAC, VEDAS, IN-SPACe, SAC Ahmedabad, ISDA PRADAN.
+- **Space Science:** Heliophysics, Solar UV Spectroscopy, Chromospheric Flares, Coronal Mass Ejections (CME), Solar Wind Plasma, Exoplanets, Kepler Light Curves, Goldilocks Habitable Zone.
+- **Earth & Marine Observation:** CalCOFI CTD casts, Sea Surface Temperature (SST), Salinity (PSU), Chlorophyll-a Biomass, Sentinel-1 C-Band SAR Radar, Microwave Backscatter ($\sigma_0$), Flood Inundation Disaster Mapping.
+- **AI & ML Architecture:** Qwen 2.5 7B, Grouped-Query Attention (GQA), Rotary Position Embeddings (RoPE 32k), GraphRAG, Retrieval Interleaved Generation (RIG), Audio Sonification.
 ---