Image-Text-to-Text
GGUF
English
Hindi
geospatial
satellite-imagery
remote-sensing
object-detection
multimodal
vision
ollama
defense
indic
sovereign-ai
Instructions to use techindro/SamyamLM-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use techindro/SamyamLM-V1 with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf techindro/SamyamLM-V1:F16 # Run inference directly in the terminal: llama cli -hf techindro/SamyamLM-V1:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf techindro/SamyamLM-V1:F16 # Run inference directly in the terminal: llama cli -hf techindro/SamyamLM-V1:F16
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf techindro/SamyamLM-V1:F16 # Run inference directly in the terminal: ./build/bin/llama cli -hf techindro/SamyamLM-V1:F16
Use Docker
docker model run hf.co/techindro/SamyamLM-V1:F16
- Llama new
- LM Studio
- Jan
- vLLM
How to use techindro/SamyamLM-V1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "techindro/SamyamLM-V1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "techindro/SamyamLM-V1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/techindro/SamyamLM-V1:F16
- Ollama
How to use techindro/SamyamLM-V1 with Ollama:
ollama run hf.co/techindro/SamyamLM-V1:F16
- Unsloth Desktop
- Docker Model Runner
How to use techindro/SamyamLM-V1 with Docker Model Runner:
docker model run hf.co/techindro/SamyamLM-V1:F16
- Lemonade
How to use techindro/SamyamLM-V1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull techindro/SamyamLM-V1:F16
Run and chat with the model
lemonade run user.SamyamLM-V1-F16
List all available models
lemonade list
- Atomic Chat
Download Modelfile from techindro/SamyamLM-V1: direct link, hf CLI and curl.
- Browser
- Download file 1.5 kB
-
https://huggingface.co/techindro/SamyamLM-V1/resolve/main/Modelfile
- Command line
-
hf download hf://techindro/SamyamLM-V1/Modelfile
-
curl -L -o Modelfile https://huggingface.co/techindro/SamyamLM-V1/resolve/main/Modelfile
1.5 kB
| # ============================================================ | |
| # SamyamLM-V1 — Multimodal Spatial Vision Model | |
| # Base: moondream (Phi-2 1.4B + CLIP ViT 454M Projector) | |
| # Publisher: techindro / Samyam Space Labels | |
| # ============================================================ | |
| FROM moondream | |
| # --- System Persona (Sovereign Dual-Language Geospatial AI) --- | |
| SYSTEM """You are SamyamLM-V1, an advanced Spatial Vision AI developed by Samyam Space Labels. | |
| Your instructions: | |
| - If a user greets you or asks who you are, introduce yourself politely: explain that you are SamyamLM-V1, developed by Samyam Space Labels for satellite imagery analysis, aerial drone monitoring, and spatial vision intelligence. | |
| - Analyze satellite imagery, aerial drone photos, and geospatial data. | |
| - Detect objects with precise normalized bounding boxes [ymin, xmin, ymax, xmax]. | |
| - Identify spatial assets: buildings, runways, roads, water bodies, solar arrays, tactical infrastructure. | |
| - Provide tactical descriptions in English and Hindi (हिन्दी). | |
| - Keep descriptions accurate, concise, and operational.""" | |
| # --- Native Phi-2 / Moondream Template --- | |
| TEMPLATE """{{ if .System }}{{ .System }} | |
| {{ end }}{{ if .Prompt }}Question: {{ .Prompt }} | |
| {{ end }}Answer: {{ .Response }}""" | |
| # --- Inference & Performance Parameters (Optimized for Fast Execution) --- | |
| PARAMETER temperature 0.2 | |
| PARAMETER top_p 0.9 | |
| PARAMETER num_ctx 2048 | |
| PARAMETER num_predict 256 | |
| PARAMETER stop "<|endoftext|>" | |
| PARAMETER stop "Question:" | |