Text Generation
Transformers
Safetensors
English
hrm_text
hrm
hierarchical-reasoning
prefix-lm
pre-alignment
non-chat
non-instruction-tuned
Instructions to use sapientinc/HRM-Text-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sapientinc/HRM-Text-1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="sapientinc/HRM-Text-1B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("sapientinc/HRM-Text-1B") model = AutoModelForCausalLM.from_pretrained("sapientinc/HRM-Text-1B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use sapientinc/HRM-Text-1B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "sapientinc/HRM-Text-1B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "sapientinc/HRM-Text-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/sapientinc/HRM-Text-1B
- SGLang
How to use sapientinc/HRM-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 "sapientinc/HRM-Text-1B" \ --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": "sapientinc/HRM-Text-1B", "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 "sapientinc/HRM-Text-1B" \ --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": "sapientinc/HRM-Text-1B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use sapientinc/HRM-Text-1B with Docker Model Runner:
docker model run hf.co/sapientinc/HRM-Text-1B
Update config.json
Browse files- config.json +2 -1
config.json
CHANGED
|
@@ -13,7 +13,8 @@
|
|
| 13 |
"H_cycles": 2,
|
| 14 |
"L_cycles": 3,
|
| 15 |
"L_bp_cycles": [
|
| 16 |
-
|
|
|
|
| 17 |
],
|
| 18 |
"max_position_embeddings": 4096,
|
| 19 |
"rms_norm_eps": 1e-06,
|
|
|
|
| 13 |
"H_cycles": 2,
|
| 14 |
"L_cycles": 3,
|
| 15 |
"L_bp_cycles": [
|
| 16 |
+
0,
|
| 17 |
+
3
|
| 18 |
],
|
| 19 |
"max_position_embeddings": 4096,
|
| 20 |
"rms_norm_eps": 1e-06,
|