text-generation-inference
CommunityDeploy LLMs with Hugging Face TGI.
Authorfgarofalo56
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides expert guidance for deploying Large Language Models (LLMs) using Hugging Face's Text Generation Inference (TGI), enabling efficient and high-throughput inference for production environments.
Core Features & Use Cases
- Production LLM Serving: Deploy LLMs for real-time applications.
- Optimized Inference: Supports quantization (bitsandbytes, GPTQ, AWQ, EETQ, FP8), continuous batching, and tensor parallelism for performance.
- Flexible Deployment: Offers Docker, Docker Compose, and Kubernetes deployment options.
- API Integration: Provides Python client, OpenAI-compatible API, and REST API for seamless integration.
- Use Case: Deploying a Llama-3.1-70B-Instruct model with 4-bit quantization and tensor parallelism to serve a high volume of user requests for text generation.
Quick Start
Deploy a basic GPU instance of Text Generation Inference using Docker with the Llama-3.1-8B-Instruct model.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
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Please help me install this Skill: Name: text-generation-inference Download link: https://github.com/fgarofalo56/Suppercharge_Microsoft_Fabric/archive/main.zip#text-generation-inference Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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