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ChatLLaMA
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ChatLLaMA Verified Tool

ChatLLaMA is a research-oriented package of LoRA weights and a desktop interface for running older LLaMA-based conversational assistants locally on compatible GPU hardware. Users should inspect model and dataset licenses, secure the local environment, understand the project’s age and limitations, test safety and accuracy and avoid unsupported production use.

Last Update: August 20, 2026

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Starting price From $3 one-time

Tool Information

ChatLLaMA is a research-oriented package of LoRA weights and a desktop interface for running older LLaMA-based conversational assistants locally on compatible GPU hardware. Users should inspect model and dataset licenses, secure the local environment, understand the project’s age and limitations, test safety and accuracy and avoid unsupported production use.

Use authorized inputs and least-privilege integrations. Configure privacy, retention, sharing, accessibility, disclosure, export, moderation and spending controls. Test representative cases, verify facts, calculations, citations, messages and media, preserve originals and retain accountable human approval before publication, outreach, deployment or operational action.

The reviewed package is sold for a $3 one-time payment and includes several model-size LoRA weight options and a desktop GUI. Hardware, base-model access, setup, support and future availability are separate.

AI output can be inaccurate, biased, derivative, insecure, incomplete or misleading. Review consent, copyright, training and retention terms, renewals, refunds, platform rules and applicable law. Education, health, finance, legal, marketing and customer-facing workflows require qualified human review.

F.A.Q (3)

ChatLLaMA is a research-oriented package of LoRA weights and a desktop interface for running older LLaMA-based conversational assistants locally on compatible GPU hardware. Users should inspect model and dataset licenses, secure the local environment, understand the project’s age and limitations, test safety and accuracy and avoid unsupported production use.

Use authorized inputs and least-privilege integrations. Configure privacy, retention, sharing, accessibility, disclosure, export, moderation and spending controls. Test representative cases, verify facts, calculations, citations, messages and media, preserve originals and retain accountable human approval before publication, outreach, deployment or operational action.

Verified pricing: From $3 one-time. The reviewed package is sold for a $3 one-time payment and includes several model-size LoRA weight options and a desktop GUI. Hardware, base-model access, setup, support and future availability are separate.

Pros and Cons

Pros

  • Runs directly on GPUs
  • Utilizes trained LoRA
  • Models conversational systems
  • Future RLHF version
  • Available in multiple models
  • Accepts user-shared datasets
  • Trainable on new datasets

Cons

  • Requires JavaScript to buy
  • Runs directly on GPUs
  • No foundation model weights
  • Designed primarily for research
  • Dependent on user data share
  • Limited to 30B; 13B; and 7B models
  • Communication mainly through Discord

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