KamoCRM + Hugging Face

Access hundreds of open models via Hugging Face Inference

Overview

Configure Hugging Face as the LLM provider for KamoCRM's AI assistant. Access hundreds of open-source models via Hugging Face's Inference Endpoints — useful for teams that want to experiment with specialized models (domain-tuned, multilingual, custom fine-tunes) without hosting infrastructure.

Common use cases

Specialized open-source models

Route to domain-specialized models (legal, medical, finance-tuned) hosted on Hugging Face.

Custom fine-tuned model deployment

If you've fine-tuned a model on your data and deployed it to HF Inference Endpoints, point KamoCRM at it.

Model experimentation

Try emerging models (often appearing on HF before commercial providers) before deciding on a primary backend.

Setup

1Sign up at huggingface.co
2Deploy your chosen model to Inference Endpoints or use serverless inference
3Navigate to Settings → AI → Providers in KamoCRM
4Select Hugging Face as a provider
5Enter your HF API token and endpoint URL
6Test with a sample query

What data syncs

AI request/response routing

Token/compute usage (billed by Hugging Face)

Model metadata

Questions about Hugging Face

Why use Hugging Face over direct providers?

Access to specialized or open-weight models not available through OpenAI/Anthropic. Useful for specific use cases or custom fine-tunes.

Serverless vs Inference Endpoints?

Serverless: pay-per-call, good for low-volume experimentation. Inference Endpoints: dedicated deployment with predictable performance, better for production workloads.

Can I use HF-hosted Llama or Mistral models?

Yes. Many open-weight models are available on HF. For Llama and Mistral specifically, consider the dedicated provider configs — same underlying models, different hosting.

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