Instructions to use jirvine/origen-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jirvine/origen-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jirvine/origen-model")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("jirvine/origen-model") model = AutoModelForCausalLM.from_pretrained("jirvine/origen-model") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use jirvine/origen-model with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jirvine/origen-model" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jirvine/origen-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/jirvine/origen-model
- SGLang
How to use jirvine/origen-model 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 "jirvine/origen-model" \ --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": "jirvine/origen-model", "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 "jirvine/origen-model" \ --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": "jirvine/origen-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use jirvine/origen-model with Docker Model Runner:
docker model run hf.co/jirvine/origen-model
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9e826e0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | {
"_name_or_path": "/content/drive/MyDrive/Science/models/doric_scratch_488147/checkpoint-40000",
"architectures": [
"RoFormerForCausalLM"
],
"attention_probs_dropout_prob": 0.1,
"embedding_size": 768,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"is_decoder": true,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 1536,
"model_type": "roformer",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"pad_token_id": 0,
"rotary_value": false,
"torch_dtype": "float32",
"transformers_version": "4.48.2",
"type_vocab_size": 2,
"use_cache": true,
"vocab_size": 145
}
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