Text Generation
Transformers
Safetensors
English
notokenlm
notoken_gen
byte-level
tokenizer-free
from-scratch
transformer
rope
small-language-model
experimental
custom_code
Instructions to use omurberaisik/NoTokenLM-Gen-3.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omurberaisik/NoTokenLM-Gen-3.5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="omurberaisik/NoTokenLM-Gen-3.5", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("omurberaisik/NoTokenLM-Gen-3.5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use omurberaisik/NoTokenLM-Gen-3.5 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "omurberaisik/NoTokenLM-Gen-3.5" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "omurberaisik/NoTokenLM-Gen-3.5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/omurberaisik/NoTokenLM-Gen-3.5
- SGLang
How to use omurberaisik/NoTokenLM-Gen-3.5 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 "omurberaisik/NoTokenLM-Gen-3.5" \ --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": "omurberaisik/NoTokenLM-Gen-3.5", "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 "omurberaisik/NoTokenLM-Gen-3.5" \ --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": "omurberaisik/NoTokenLM-Gen-3.5", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use omurberaisik/NoTokenLM-Gen-3.5 with Docker Model Runner:
docker model run hf.co/omurberaisik/NoTokenLM-Gen-3.5
Gen-3.5: real transformers integration (AutoModel/AutoTokenizer/pipeline) + safetensors + model card
0dda19f verified 
- Xet hash:
- a3091179e60ae6cd7800fe15113c43f2b0ca48df2359dc85688797069cb632ca
- Size of remote file:
- 1.26 MB
- SHA256:
- 337ae21bd28382d9a78ae74f1a8142262803fb5d3ed114a7aaa8c377b429c77b
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