Instructions to use OpenNLG/OpenBA-V1-Based with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenNLG/OpenBA-V1-Based with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OpenNLG/OpenBA-V1-Based", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenNLG/OpenBA-V1-Based", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OpenNLG/OpenBA-V1-Based with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenNLG/OpenBA-V1-Based" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenNLG/OpenBA-V1-Based", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/OpenNLG/OpenBA-V1-Based
- SGLang
How to use OpenNLG/OpenBA-V1-Based 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 "OpenNLG/OpenBA-V1-Based" \ --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": "OpenNLG/OpenBA-V1-Based", "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 "OpenNLG/OpenBA-V1-Based" \ --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": "OpenNLG/OpenBA-V1-Based", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use OpenNLG/OpenBA-V1-Based with Docker Model Runner:
docker model run hf.co/OpenNLG/OpenBA-V1-Based
File size: 1,006 Bytes
79a1f2e | 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 28 29 30 31 32 33 34 35 36 | {
"add_ffn_bias": false,
"add_lm_head_bias": true,
"add_qkv_bias": true,
"architectures": [
"OpenBAForConditionalGeneration"
],
"auto_map": {
"AutoConfig": "configuration_openba.OpenBAConfig",
"AutoModel": "modeling_openba.OpenBAForConditionalGeneration",
"AutoModelForCausalLM": "modeling_openba.OpenBAForConditionalGeneration",
"AutoModelForSeq2SeqLM": "modeling_openba.OpenBAForConditionalGeneration"
},
"attention_dropout": 0.1,
"decoder_max_seq_length": 1024,
"decoder_start_token_id": 0,
"eos_token_id": 1,
"ffn_hidden_size": 16384,
"hidden_dropout": 0.1,
"hidden_size": 4096,
"initializer_factor": 1.0,
"is_encoder_decoder": true,
"kv_channels": 128,
"max_seq_length": 1024,
"model_type": "openba",
"num_decoder_layers": 36,
"num_heads": 40,
"num_layers": 12,
"pad_token_id": 0,
"tie_word_embeddings": false,
"tokenizer_class": "OpenBATokenizer",
"transformers_version": "4.31.0",
"use_cache": true,
"vocab_size": 250368
}
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