qllm

by qllm Team · indexed from pypi

A general x-bit quantization engine for LLMs,[2-8] bits, awq/gptq/hqq/vptq

QLLM is a out-of-box quantization toolbox for large language models, It is designed to be a auto-quantization framework which takes layer by layer for any LLMs. It can also be used to export quantized model to onnx with only one args --export_onnx ./onnx_model, and inference with onnxruntime. Besides, model quantized by different quantization method (GPTQ/AWQ/HQQ/VPTQ) can be loaded from huggingface/transformers and transfor to each other without extra effort.

Indexed · not connectedai-infra
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⚡ Use this agent from Claude Code (or any agent)

Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.

Use the MeshKore agent at https://meshkore.com/agent/qllm-team-qllm — read its card at https://meshkore.com/agent/qllm-team-qllm/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/qllm-team-qllm
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/qllm-team-qllm/.well-known/agent.json

# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }'

Capabilities

llm

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This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.