Instructions to use goodarzilab/decodon-200M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use goodarzilab/decodon-200M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="goodarzilab/decodon-200M", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("goodarzilab/decodon-200M", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use goodarzilab/decodon-200M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "goodarzilab/decodon-200M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "goodarzilab/decodon-200M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/goodarzilab/decodon-200M
- SGLang
How to use goodarzilab/decodon-200M 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 "goodarzilab/decodon-200M" \ --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": "goodarzilab/decodon-200M", "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 "goodarzilab/decodon-200M" \ --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": "goodarzilab/decodon-200M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use goodarzilab/decodon-200M with Docker Model Runner:
docker model run hf.co/goodarzilab/decodon-200M
Upload DeCodon
Browse files- config.json +1 -0
- configuration_decodon.py +2 -0
config.json
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"layer_norm_eps": 1e-12,
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"lm_type": "distilled",
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"max_position_embeddings": 2048,
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"num_attention_heads": 16,
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"num_hidden_layers": 12,
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"pad_token_id": 3,
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"layer_norm_eps": 1e-12,
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"lm_type": "distilled",
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"max_position_embeddings": 2048,
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"model_type": "decodon",
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"num_attention_heads": 16,
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"num_hidden_layers": 12,
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"pad_token_id": 3,
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configuration_decodon.py
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from transformers import PretrainedConfig
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class DeCodonConfig(PretrainedConfig):
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def __init__(
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self,
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vocab_size=70,
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from transformers import PretrainedConfig
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class DeCodonConfig(PretrainedConfig):
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model_type = "decodon"
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def __init__(
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self,
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vocab_size=70,
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