Instructions to use summerMC/TRM-textV2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use summerMC/TRM-textV2 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="summerMC/TRM-textV2", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("summerMC/TRM-textV2", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use summerMC/TRM-textV2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "summerMC/TRM-textV2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "summerMC/TRM-textV2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/summerMC/TRM-textV2

SGLang

How to use summerMC/TRM-textV2 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "summerMC/TRM-textV2" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "summerMC/TRM-textV2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "summerMC/TRM-textV2" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "summerMC/TRM-textV2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use summerMC/TRM-textV2 with Docker Model Runner:
```
docker model run hf.co/summerMC/TRM-textV2
```

TRM-textV2 / config.json

summerMC

v19: Fix tied weights and lm_head loading

1e48517 verified 29 days ago

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	{
	"auto_map": {
	"AutoConfig": "configuration_trm_text_ism.TRMTextISMConfig",
	"AutoModelForCausalLM": "modeling_trm_text_ism.TRMTextISMForCausalLM"
	},
	"bos_token_id": null,
	"dim": 768,
	"dropout": 0.0,
	"eos_token_id": null,
	"gate_init": -1.5,
	"gate_style": "stable",
	"head_dim": 64,
	"max_seq_len": 512,
	"mlp_hidden_size": null,
	"mlp_ratio": 2.6666666667,
	"model_type": "trm_text_ism",
	"n_heads": 12,
	"pad_token_id": null,
	"recurrence_steps": 4,
	"residual_scale": 0.5,
	"tie_word_embeddings": true,
	"transformers_version": "5.10.2",
	"vocab_size": 50257
	}