Text Generation
Transformers
Safetensors
PyTorch
English
Japanese
trm_text_ism
recurrent-depth
causal-lm
trm-text
conversational
custom_code
Instructions to use summerMC/Trm-text-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use summerMC/Trm-text-1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="summerMC/Trm-text-1B", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("summerMC/Trm-text-1B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use summerMC/Trm-text-1B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "summerMC/Trm-text-1B" # 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-text-1B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/summerMC/Trm-text-1B
- SGLang
How to use summerMC/Trm-text-1B 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-text-1B" \ --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-text-1B", "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-text-1B" \ --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-text-1B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use summerMC/Trm-text-1B with Docker Model Runner:
docker model run hf.co/summerMC/Trm-text-1B
| { | |
| "architectures": [ | |
| "TRMTextISMForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "modeling_trm_text_ism.TRMTextISMConfig", | |
| "AutoModelForCausalLM": "modeling_trm_text_ism.TRMTextISMForCausalLM" | |
| }, | |
| "bos_token_id": null, | |
| "dim": 2048, | |
| "dtype": "float32", | |
| "eos_token_id": 151643, | |
| "head_dim": 128, | |
| "max_seq_len": 1024, | |
| "mlp_hidden_size": 5632, | |
| "mlp_ratio": 2.6875, | |
| "model_type": "trm_text_ism", | |
| "n_heads": 16, | |
| "n_layers": 8, | |
| "pad_token_id": 151643, | |
| "recurrence_steps": 4, | |
| "residual_scale": 1.0, | |
| "tie_word_embeddings": false, | |
| "transformers_version": "5.10.2", | |
| "use_cache": false, | |
| "vocab_size": 151680 | |
| } | |