Application overview

This record describes the model checkpoint hosted by Meta's Hugging Face organization. The hosting page shows the model card, files, terms, and usage notes. Weights access requires signing in and accepting the model's conditions; MCR Tech does not mirror or download the model files.

Typical use cases

Instruction-following text generation; check Meta's stated intended use and acceptable use policy.

DeveloperMeta

GPU supportHardware requirements vary with precision, context length, runtime, and quantization; this directory does not state a minimum GPU requirement.

LicenseLlama 3.1 Community License (custom terms; not a permissive OSI license)

License referenceProject license ↗

Model card / weightsOpen official model page ↗

Model detailsLlama 3.1 · 8B parameters · Safetensors and PyTorch formats shown on the model card; available files can change.
Gated hosting page: sign in, share requested contact information, and accept the Llama 3.1 Community License and acceptable-use terms before accessing weights. Review commercial and redistribution terms yourself.

HPC compatibility

Compatibility details shown here reflect administrator-maintained project information. Review the upstream release documentation against your exact operating system, drivers, accelerator, MPI stack, and cluster policy before deployment.

Hardware requirements vary with precision, context length, runtime, and quantization; this directory does not state a minimum GPU requirement.

Installation instructions

Commands are project-specific notes. Confirm prerequisites and linked upstream instructions for your own release and system. Do not run administrative commands without review.

Python virtual environment

Prepare Python dependencies (no model weights)

Prerequisites: Python, venv, and a compatible PyTorch build selected for your system

python -m venv .venv
# Linux / macOS: source .venv/bin/activate
# Windows PowerShell: .venv\Scripts\Activate.ps1
python -m pip install transformers accelerate
python -c "import transformers, accelerate; print(transformers.__version__)"

Installs Python libraries only. This step does not log in to Hugging Face or download Llama weights.

Verify: python -c "import transformers, accelerate; print(transformers.__version__)"

Review: Model inference can download several gigabytes and uses accelerator memory. First open the gated model card, accept its terms, plan storage and hardware, then follow the current model/runtime guide. Do not place access tokens in commands, website forms, or shared logs.

Documentation for these steps ↗

Upstream references

Project homepage ↗
Source repository ↗ Link status: Verified
Documentation ↗

Link details last reviewed 2026-10-12 by MCR Tech. Project versions, licenses, hardware behavior, and hosted model access can change; follow current upstream terms.

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