Text Generation
Transformers
Safetensors
PyTorch
English
modern_dense_mha_gated_ffn_router
custom_code
causal-lm
small-language-model
babylm
strict-small
swiglu
research
Instructions to use AwakeningOS/VISTA-24M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AwakeningOS/VISTA-24M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AwakeningOS/VISTA-24M", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("AwakeningOS/VISTA-24M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use AwakeningOS/VISTA-24M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AwakeningOS/VISTA-24M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AwakeningOS/VISTA-24M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/AwakeningOS/VISTA-24M
- SGLang
How to use AwakeningOS/VISTA-24M 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 "AwakeningOS/VISTA-24M" \ --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": "AwakeningOS/VISTA-24M", "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 "AwakeningOS/VISTA-24M" \ --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": "AwakeningOS/VISTA-24M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use AwakeningOS/VISTA-24M with Docker Model Runner:
docker model run hf.co/AwakeningOS/VISTA-24M
Release VISTA-24M: model, architecture diagrams, training recipe and evaluation evidence
9287d39 verified | words_m,blimp_filtered,supplement_filtered,ewok_filtered,entity_tracking,comps,global_piqa_parallel,global_piqa_nonparallel,six_task_mean | |
| 10,65.33,57.34,49.8,17.78,49.82,23.3,43.0,45.53666666666666 | |
| 20,67.45,56.46,49.97,18.26,51.01,20.39,48.0,46.22416666666667 | |
| 30,67.11,57.17,50.61,18.57,51.41,23.3,46.0,46.586666666666666 | |
| 40,68.0,56.46,51.19,17.98,51.41,22.33,48.0,46.70083333333333 | |
| 50,68.62,55.74,51.17,18.58,51.52,26.21,46.0,46.95583333333334 | |
| 60,67.84,55.73,51.71,18.56,51.86,22.33,45.0,46.560833333333335 | |
| 70,67.67,55.8,51.83,17.97,51.48,27.18,46.0,46.89000000000001 | |
| 80,67.73,58.41,52.83,18.56,51.32,28.16,51.0,48.071666666666665 | |
| 90,67.34,55.9,51.99,18.16,51.45,23.3,47.0,46.665 | |
| 100,67.41,56.27,51.89,18.26,51.25,24.27,46.0,46.70250000000001 | |