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HuggingChat

HuggingChat is Hugging Face's open-source chat interface for conversing with open models from the Hugging Face ecosystem.

WritingCodingResearch

How it works / How to use

HuggingChat is Hugging Face's open-source chat interface for conversing with open models from the Hugging Face ecosystem.

  1. Open HuggingChat and start a new conversation.
  2. State your goal, audience, and desired output format up front.
  3. Provide only the context needed; ask follow-ups in the same thread to refine.
  4. Verify important facts against cited or linked sources when accuracy matters.

How to prompt

HuggingChat provides easy access to compare open-source chat models.

Explain the difference between LoRA and full fine-tuning for LLMs in five sentences.

Best output tips

  • Lead with role, audience, and output format in one message.
  • Ask for citations or step-by-step reasoning when accuracy matters.
  • Do not paste secrets or regulated data unless your plan allows it.
  • Verify current plans and limits on the official HuggingChat website.

Try this AI

Try HuggingChat

Product Details

Pricing, features, limits and latest updates

HuggingChat

HuggingChat is Hugging Face's open-source chat interface for conversing with open models from the Hugging Face ecosystem.

No listed price

Pricing Plans

No listed plans.

Key Features

Chat

chat workflow (huggingface.co).

Open Source

open source workflow (huggingface.co).

Ideas / Prompt experiences

Share a prompt that worked for you. Username and email are shown with your submission. External links are not allowed.

Example prompt

Try an open model

Prompt

Explain the difference between LoRA and full fine-tuning for LLMs in five sentences.

Short explanation

HuggingChat provides easy access to compare open-source chat models.

Example prompt

Code generation

Prompt

Write a Python function to parse CSV files and return summary statistics for numeric columns.

Short explanation

Open models on HuggingChat support general coding and Q&A tasks.

Share your experience

Required fields are marked. Variation, result, and explanation are optional.

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