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
File size: 1,502 Bytes
ed36197 1b9c588 ed36197 d80d126 ed36197 d80d126 ed36197 1b9c588 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | # ============================================================
# 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:"
|