Mistral

Mistral AI models are efficient transformer decoder models featuring sliding window attention for long context support. Mistral-Nemo is a 12B model developed jointly with NVIDIA.


Task	Text Generation
Architecture	`MistralForCausalLM`
Parameters	7B – 12B
HF Org	mistralai

Available Models

Mistral-7B: v0.1, v0.2, v0.3
Mistral-7B-Instruct: v0.1, v0.2, v0.3
Mistral-Nemo-Instruct-2407: 12B

Architecture

MistralForCausalLM

Example HF Models

Model	HF ID
Mistral 7B v0.1	`mistralai/Mistral-7B-v0.1`
Mistral 7B Instruct v0.1	`mistralai/Mistral-7B-Instruct-v0.1`
Mistral Nemo Instruct 2407	`mistralai/Mistral-Nemo-Instruct-2407`

Example Recipes

Recipe	Description
mistral_7b_squad.yaml	SFT — Mistral 7B on SQuAD
mistral_7b_squad_peft.yaml	LoRA — Mistral 7B on SQuAD
mistral_nemo_2407_squad.yaml	SFT — Mistral Nemo 2407 on SQuAD
mistral_nemo_2407_squad_peft.yaml	LoRA — Mistral Nemo 2407 on SQuAD

Try with NeMo AutoModel

1. Install (full instructions):

$ pip install nemo-automodel

2. Clone the repo to get the example recipes:

$ git clone https://github.com/NVIDIA-NeMo/Automodel.git
$ cd Automodel

3. Run the recipe from inside the repo:

$ automodel --nproc-per-node=8 examples/llm_finetune/mistral/mistral_7b_squad.yaml

Run with Docker

1. Pull the container and mount a checkpoint directory:

$ docker run --gpus all -it --rm \
>   --shm-size=8g \
>   -v $(pwd)/checkpoints:/opt/Automodel/checkpoints \
>   nvcr.io/nvidia/nemo-automodel:26.06.00

2. Navigate to the AutoModel directory (where the recipes are):

$ cd /opt/Automodel

3. Run the recipe:

$ automodel --nproc-per-node=8 examples/llm_finetune/mistral/mistral_7b_squad.yaml

See the Installation Guide and LLM Fine-Tuning Guide.

Fine-Tuning

See the LLM Fine-Tuning Guide.