Model CoverageLarge Language Models (LLMs)

InternLM

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InternLM is a bilingual (Chinese-English) language model series from Shanghai AI Laboratory, with versions 1, 2, and 3 each improving on reasoning, instruction following, and long-context capabilities.

TaskText Generation
ArchitectureInternLMForCausalLM / InternLM2ForCausalLM / InternLM3ForCausalLM
Parameters7B – 8B
HF Orginternlm

Available Models

  • InternLM3-8B-Instruct (InternLM3)
  • InternLM2-7B, InternLM2-Chat-7B (InternLM2)
  • InternLM-7B, InternLM-Chat-7B (InternLM v1)

Architectures

  • InternLMForCausalLM — InternLM v1
  • InternLM2ForCausalLM — InternLM2
  • InternLM3ForCausalLM — InternLM3

Example HF Models

ModelHF ID
InternLM3 8B Instructinternlm/internlm3-8b-instruct
InternLM2 7Binternlm/internlm2-7b
InternLM 7Binternlm/internlm-7b

Try with NeMo AutoModel

Install NeMo AutoModel and follow the fine-tuning guide to configure a recipe for this model.

1. Install (full instructions):

$pip install nemo-automodel

2. Clone the repo to get example recipes you can adapt:

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

3. Fine-tune by adapting a base LLM recipe — override the model ID on the CLI:

$automodel --nproc-per-node=8 examples/llm_finetune/llama3_2/llama3_2_1b_squad.yaml \
>  --model.pretrained_model_name_or_path <MODEL_HF_ID>

Replace <MODEL_HF_ID> with the model ID from Example HF Models above.

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:26.04.00

2. The recipes are at /opt/Automodel/examples/ — navigate there:

$cd /opt/Automodel

3. Fine-tune:

$automodel --nproc-per-node=8 examples/llm_finetune/llama3_2/llama3_2_1b_squad.yaml \
>  --model.pretrained_model_name_or_path <MODEL_HF_ID>

See the Installation Guide and LLM Fine-Tuning Guide.

Fine-Tuning

See the LLM Fine-Tuning Guide.

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