Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit
Built by Agnuxo, Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit is a 7 billion parameter chat model. Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit is an open-weights chat model with roughly 7 billion parameters.
by Agnuxo · 7B parameters
Best for
Ways to use Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your Agnuxo API key. osFoundry discovers Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit automatically — assign it to a Maestro role (router, direct, orchestrator, or fallback) in the Pipeline tab and it is live in every chat. Your key, your provider account — no token markup.
Deploy a dedicated endpoint
Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit is open-weights — run it locally for free, or deploy a dedicated GPU endpoint in your workspace for reserved capacity with no rate limits.
Use it in a Room App
Room Apps declare AI features in their manifest, then call them with invokeAI:
import { invokeAI } from '@osfoundry/app-sdk'
// 'summarize' is an AI feature declared in your app manifest.
const result = await invokeAI('summarize', userText)
Call it from your own apps
Once a model is wired into your workspace you can host it as an API and reach it from your own services, scripts, or CI — outside osFoundry.
What hardware can run Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit
Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit runs on a single 16GB consumer GPU (~5 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~17 GB).
Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit
Is Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit free to use?
Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit is free to run locally on your own hardware. Hosted access through osFoundry is metered (input Free (local), output Free (local)). You can switch between local and hosted at any time.
Can I use Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
How much VRAM does Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit need?
Approximately 5 GB at Q4 quantisation, or 17 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit locally?
Yes. Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit best at?
Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit is well-suited to text generation.
How do I use Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit in osFoundry?
Paste your Agnuxo API key in the key dialog (or deploy the open weights for self-hostable models), assign Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by Agnuxo on September 1, 2024. Source: https://huggingface.co/Agnuxo/Tinytron-ORCA-7B-TinyLlama-Instruct_CODE_Python-extra_small_quantization_GGUF_3bit