Text Generation
Transformers
Safetensors
llama
toksuite
tokenization
tokenmonster
subword
research
robustness
text-generation-inference
Instructions to use toksuite/tokenmonster-englishcode-32000-consistent-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toksuite/tokenmonster-englishcode-32000-consistent-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="toksuite/tokenmonster-englishcode-32000-consistent-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("toksuite/tokenmonster-englishcode-32000-consistent-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use toksuite/tokenmonster-englishcode-32000-consistent-v1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "toksuite/tokenmonster-englishcode-32000-consistent-v1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "toksuite/tokenmonster-englishcode-32000-consistent-v1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/toksuite/tokenmonster-englishcode-32000-consistent-v1
- SGLang
How to use toksuite/tokenmonster-englishcode-32000-consistent-v1 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 "toksuite/tokenmonster-englishcode-32000-consistent-v1" \ --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": "toksuite/tokenmonster-englishcode-32000-consistent-v1", "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 "toksuite/tokenmonster-englishcode-32000-consistent-v1" \ --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": "toksuite/tokenmonster-englishcode-32000-consistent-v1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use toksuite/tokenmonster-englishcode-32000-consistent-v1 with Docker Model Runner:
docker model run hf.co/toksuite/tokenmonster-englishcode-32000-consistent-v1
Download toksuite-logo.png from toksuite/tokenmonster-englishcode-32000-consistent-v1: direct link, hf CLI and curl.
- Browser
- Download file 1 MB
-
https://huggingface.co/toksuite/tokenmonster-englishcode-32000-consistent-v1/resolve/main/toksuite-logo.png
- Command line
-
hf download hf://toksuite/tokenmonster-englishcode-32000-consistent-v1/toksuite-logo.png
-
curl -L -o toksuite-logo.png https://huggingface.co/toksuite/tokenmonster-englishcode-32000-consistent-v1/resolve/main/toksuite-logo.png
1 MB

- Xet hash:
- 7d006276ae2f1794e3512603921dd8f6318cece29a1faea75804ef14a9b5d846
- Size of remote file:
- 1 MB
- SHA256:
- 2c53933c8447aa96b6ab87de42ce8a7cf913132f71f06df162f05644004d2806
·
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