Instructions to use yujiepan/hrm-text-tiny-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yujiepan/hrm-text-tiny-random with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="yujiepan/hrm-text-tiny-random")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("yujiepan/hrm-text-tiny-random") model = AutoModelForCausalLM.from_pretrained("yujiepan/hrm-text-tiny-random", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use yujiepan/hrm-text-tiny-random with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "yujiepan/hrm-text-tiny-random" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yujiepan/hrm-text-tiny-random", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/yujiepan/hrm-text-tiny-random
- SGLang
How to use yujiepan/hrm-text-tiny-random 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 "yujiepan/hrm-text-tiny-random" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yujiepan/hrm-text-tiny-random", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "yujiepan/hrm-text-tiny-random" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yujiepan/hrm-text-tiny-random", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use yujiepan/hrm-text-tiny-random with Docker Model Runner:
docker model run hf.co/yujiepan/hrm-text-tiny-random
Download config.json from yujiepan/hrm-text-tiny-random: direct link, hf CLI and curl.
- Browser
- Download file 877 Bytes
-
https://huggingface.co/yujiepan/hrm-text-tiny-random/resolve/main/config.json
- Command line
-
hf download hf://yujiepan/hrm-text-tiny-random/config.json
-
curl -L -o config.json https://huggingface.co/yujiepan/hrm-text-tiny-random/resolve/main/config.json
877 Bytes
| { | |
| "H_cycles": 2, | |
| "L_bp_cycles": [ | |
| 0, | |
| 3 | |
| ], | |
| "L_cycles": 3, | |
| "architectures": [ | |
| "HrmTextForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 6, | |
| "dtype": "bfloat16", | |
| "embedding_scale": 39.191835884530846, | |
| "eos_token_id": 11, | |
| "head_dim": 32, | |
| "hidden_act": "silu", | |
| "hidden_size": 8, | |
| "initializer_range": 0.025515518153991442, | |
| "intermediate_size": 64, | |
| "max_position_embeddings": 4096, | |
| "mlp_bias": false, | |
| "model_type": "hrm_text", | |
| "num_attention_heads": 4, | |
| "num_hidden_layers": 64, | |
| "num_key_value_heads": 4, | |
| "num_layers_per_stack": 8, | |
| "pad_token_id": 5, | |
| "prefix_lm": true, | |
| "rms_norm_eps": 1e-06, | |
| "rope_parameters": { | |
| "rope_theta": 10000.0, | |
| "rope_type": "default" | |
| }, | |
| "tie_word_embeddings": false, | |
| "transformers_version": "5.9.0", | |
| "use_cache": true, | |
| "vocab_size": 65536 | |
| } | |