Text Generation
Transformers
TensorBoard
Safetensors
gemma2
Generated from Trainer
text-generation-inference
Instructions to use JuIm/ProteinLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JuIm/ProteinLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="JuIm/ProteinLM")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("JuIm/ProteinLM") model = AutoModelForCausalLM.from_pretrained("JuIm/ProteinLM") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use JuIm/ProteinLM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "JuIm/ProteinLM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "JuIm/ProteinLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/JuIm/ProteinLM
- SGLang
How to use JuIm/ProteinLM 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 "JuIm/ProteinLM" \ --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": "JuIm/ProteinLM", "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 "JuIm/ProteinLM" \ --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": "JuIm/ProteinLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use JuIm/ProteinLM with Docker Model Runner:
docker model run hf.co/JuIm/ProteinLM
Upload Gemma2ForCausalLM
Browse files- config.json +4 -4
- model.safetensors +2 -2
config.json
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"hidden_activation": "gelu_pytorch_tanh",
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"intermediate_size":
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"max_position_embeddings": 512,
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"model_type": "gemma2",
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"pad_token_id": 22,
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"query_pre_attn_scalar": 224,
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"rms_norm_eps": 1e-06,
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"hidden_activation": "gelu_pytorch_tanh",
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"max_position_embeddings": 512,
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"model_type": "gemma2",
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"num_attention_heads": 8,
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"num_hidden_layers": 16,
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"num_key_value_heads": 8,
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"pad_token_id": 22,
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"query_pre_attn_scalar": 224,
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"rms_norm_eps": 1e-06,
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model.safetensors
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size 1342562152
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