Instructions to use PramodSeeram/BFSI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use PramodSeeram/BFSI with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="PramodSeeram/BFSI",
	filename="astra-llm.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use PramodSeeram/BFSI with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf PramodSeeram/BFSI
# Run inference directly in the terminal:
llama-cli -hf PramodSeeram/BFSI

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf PramodSeeram/BFSI
# Run inference directly in the terminal:
llama-cli -hf PramodSeeram/BFSI

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf PramodSeeram/BFSI
# Run inference directly in the terminal:
./llama-cli -hf PramodSeeram/BFSI

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf PramodSeeram/BFSI
# Run inference directly in the terminal:
./build/bin/llama-cli -hf PramodSeeram/BFSI

Use Docker

docker model run hf.co/PramodSeeram/BFSI

LM Studio
Jan
Ollama
How to use PramodSeeram/BFSI with Ollama:
```
ollama run hf.co/PramodSeeram/BFSI
```

Unsloth Studio new

How to use PramodSeeram/BFSI with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for PramodSeeram/BFSI to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for PramodSeeram/BFSI to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for PramodSeeram/BFSI to start chatting

Docker Model Runner
How to use PramodSeeram/BFSI with Docker Model Runner:
```
docker model run hf.co/PramodSeeram/BFSI
```

Lemonade

How to use PramodSeeram/BFSI with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull PramodSeeram/BFSI

Run and chat with the model

lemonade run user.BFSI-{{QUANT_TAG}}

List all available models

lemonade list

PramodSeeram commited on 26 days ago

Commit

bdc8db4

verified ·

1 Parent(s): 601fa6b

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+# Astra LLM (BFSI Domain)
+## Overview
+A domain-adapted Large Language Model built on Mistral 7B, fine-tuned using LoRA for financial intelligence tasks.
+## Capabilities
+- Credit card optimization
+- Financial insights & recommendations
+- Fraud/scam reasoning
+- Insurance claim understanding
+## Architecture
+- Base Model: Mistral 7B
+- Fine-tuning: LoRA
+- Deployment: Ollama
+- Format: GGUF
+## Integration
+- RAG with Qdrant
+- Multi-agent orchestration (LangGraph)
+- Used in Astra 360 Digital Brain
+## Usage (Ollama)
+ollama run astra-llm
+## Author
+Pramod Seeram