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Independent publisher

Sriram Ramakrishnan

sriram1983007

Interested in translating modern ML capabilities into intuitive product solutions. Particularly focused on predictive analytics for customer retention/personalization, conversational AI user experience, and establishing clear ROI metrics for enterprise AI tooling.

Models in Library2
Datasets in Library0
Models on Hugging Face4
Followers1

Models

Model · Text generation

SRA-RiskGate-4B

Sriram Ramakrishnan

SRA-RiskGate-4B is an autonomous risk scoring, compliance verification, and dispute adjudication model fine-tuned on top of Qwen/Qwen3-4B-Instruct-2507. It is engineered for both ends of a stablecoin payment's operational lifecycle: Autonomous on-chain agents can hallucinate payment transfers, sign malformed calldata, or trigger catastrophic transactions during market depegs. The deterministic pre-filter and policy firewall is available directly as a verified Action Provider for the Coinbase AgentKit framework: Register RiskGateActionProvider as the payment provider on your AgentKit instance. It checks chain support, policies, and peg deviations, executing safe ERC-20 transfers only after…

Open weights apache-2.0 4B parameters 262,144 tokens transformers

This repository contains the quantized GGUF weights (Q4KM, ~2.5 GB) for SRA-RiskGate-4B, an autonomous risk scoring, compliance verification, and dispute resolution agent for stablecoin payments (EIP-3009, x402, smart escrow). Deploying with autonomous on-chain agents or payment gateways? Use the companion Python SDK for zero-latency deterministic pre-filtering (sanctions, address validation, depeg protection) and drop-in Coinbase AgentKit firewall support: Note: Always run with greedy decoding (--temp 0.0) to guarantee deterministic JSON output conforming to the benchmark schema. Distributed under the Apache 2.0 License.

Open weights apache-2.0 gguf