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 |
|
Parameters |
7B – 12B |
HF Org |
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 |
|
Mistral 7B Instruct v0.1 |
|
Mistral Nemo Instruct 2407 |
Example Recipes#
Recipe |
Description |
|---|---|
SFT — Mistral 7B on SQuAD |
|
LoRA — Mistral 7B on SQuAD |
|
SFT — Mistral Nemo 2407 on SQuAD |
|
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:26.02.00
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.