> This page is for version 0.7.0 · 26.10.
> For other versions, use one of these documentation indexes:
> - Nightly (default): https://docs.nvidia.com/nemo/automodel/nightly/llms.txt
> - Latest: https://docs.nvidia.com/nemo/automodel/latest/llms.txt
> - 0.7.0 · 26.10: https://docs.nvidia.com/nemo/automodel/v0.7/llms.txt
> - 0.5.0 · 26.06: https://docs.nvidia.com/nemo/automodel/v0.5/llms.txt
> - 0.4.0 · 26.04: https://docs.nvidia.com/nemo/automodel/v0.4/llms.txt

> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/automodel/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/automodel/_mcp/server.

# Llama-3.1-70B

> Use NeMo AutoModel to fine-tune Llama-3.1-70B for LLM workflows with checked-in text generation recipes and documented distributed settings.

[Llama-3.1-70B](https://huggingface.co/meta-llama/Llama-3.1-70B) has a checked-in NeMo AutoModel recipe for text generation.
The Hugging Face configuration declares the `LlamaForCausalLM` architecture.

## Fine-Tune Llama-3.1-70B

Follow the [installation instructions](/nemo/automodel/v0.7/get-started/installation), then review the checked-in recipe and
its declared topology below before choosing a local or cluster launcher.

## Choose a Workflow

| Goal                                         | Start Here                                                                                                                                                           |
| -------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Run the primary recipe for this model        | Use the [recipe configuration](https://github.com/NVIDIA-NeMo/Automodel/blob/r0.7.0/examples/llm_pretrain/llama3_70b_pretrain.yaml).                                 |
| Try another checked-in recipe for this model | Use the [alternate recipe](https://github.com/NVIDIA-NeMo/Automodel/blob/r0.7.0/examples/llm_benchmark/llama3_3/custom_llama3_1_70b_pretrain_benchmark_8nodes.yaml). |

### Configuration

| Setting  | Configuration                                                                                          |
| -------- | ------------------------------------------------------------------------------------------------------ |
| Hardware | -                                                                                                      |
| Strategy | FSDP2; tp_size=4, pp_size=4, cp_size=1                                                                 |
| Nodes    | -                                                                                                      |
| Features | Activation checkpointing (activation_checkpointing=true), Packed sequences (packed_sequence_size=4096) |
| Advanced | bfloat16                                                                                               |

### More Recipes for This Model

* [`custom_llama3_1_70b_pretrain_benchmark_8nodes.yaml`](https://github.com/NVIDIA-NeMo/Automodel/blob/r0.7.0/examples/llm_benchmark/llama3_3/custom_llama3_1_70b_pretrain_benchmark_8nodes.yaml)

## Model Reference

### Model Architecture

| Property     | Value              |
| ------------ | ------------------ |
| Task         | Text generation    |
| Architecture | `LlamaForCausalLM` |

### Available Models

* [`meta-llama/Llama-3.1-70B`](https://huggingface.co/meta-llama/Llama-3.1-70B)

## Related Resources

* [LLM fine-tuning guide](/nemo/automodel/v0.7/recipes-e2e-examples/sft-peft)