Instructions to use DedsecurityAI/dpt-125mb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DedsecurityAI/dpt-125mb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="DedsecurityAI/dpt-125mb")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("DedsecurityAI/dpt-125mb") model = AutoModelForCausalLM.from_pretrained("DedsecurityAI/dpt-125mb") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use DedsecurityAI/dpt-125mb with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DedsecurityAI/dpt-125mb" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DedsecurityAI/dpt-125mb", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/DedsecurityAI/dpt-125mb
- SGLang
How to use DedsecurityAI/dpt-125mb 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 "DedsecurityAI/dpt-125mb" \ --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": "DedsecurityAI/dpt-125mb", "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 "DedsecurityAI/dpt-125mb" \ --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": "DedsecurityAI/dpt-125mb", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use DedsecurityAI/dpt-125mb with Docker Model Runner:
docker model run hf.co/DedsecurityAI/dpt-125mb
Commit ·
b9fb54e
1
Parent(s): 3e86c27
Upload config.json
Browse files- config.json +27 -0
config.json
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{
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"activation_dropout": 0.0,
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"activation_function": "relu",
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"architectures": [
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"OPTForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 0,
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"hidden_size": 768,
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"do_layer_norm_before": true,
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"dropout": 0.1,
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"eos_token_id": 2,
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"ffn_dim": 3072,
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"init_std": 0.02,
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"layerdrop": 0.0,
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"max_position_embeddings": 2048,
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"model_type": "opt",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"torch_dtype": "float16",
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"transformers_version": "4.19.0.dev0",
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"use_cache": true,
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"vocab_size": 50272,
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"word_embed_proj_dim": 768,
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"prefix": "</s>"
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}
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