Text Generation
Transformers
PyTorch
gpt_neox
text-generation-inference
8-bit precision
bitsandbytes
Instructions to use jionlyu/3B-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jionlyu/3B-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jionlyu/3B-test")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("jionlyu/3B-test") model = AutoModelForCausalLM.from_pretrained("jionlyu/3B-test") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use jionlyu/3B-test with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jionlyu/3B-test" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jionlyu/3B-test", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/jionlyu/3B-test
- SGLang
How to use jionlyu/3B-test 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 "jionlyu/3B-test" \ --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": "jionlyu/3B-test", "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 "jionlyu/3B-test" \ --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": "jionlyu/3B-test", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use jionlyu/3B-test with Docker Model Runner:
docker model run hf.co/jionlyu/3B-test
| { | |
| "_name_or_path": "togethercomputer/RedPajama-INCITE-Chat-3B-v1", | |
| "architectures": [ | |
| "GPTNeoXForCausalLM" | |
| ], | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 0, | |
| "classifier_dropout": 0.1, | |
| "eos_token_id": 0, | |
| "hidden_act": "gelu", | |
| "hidden_dropout": 0.0, | |
| "hidden_size": 2560, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 10240, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 2048, | |
| "model_type": "gpt_neox", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "quantization_config": { | |
| "bnb_4bit_compute_dtype": "float32", | |
| "bnb_4bit_quant_type": "fp4", | |
| "bnb_4bit_use_double_quant": false, | |
| "llm_int8_enable_fp32_cpu_offload": false, | |
| "llm_int8_has_fp16_weight": false, | |
| "llm_int8_skip_modules": null, | |
| "llm_int8_threshold": 6.0, | |
| "load_in_4bit": false, | |
| "load_in_8bit": true, | |
| "quant_method": "bitsandbytes" | |
| }, | |
| "rope_scaling": null, | |
| "rotary_emb_base": 10000, | |
| "rotary_pct": 1.0, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.32.0.dev0", | |
| "use_cache": true, | |
| "use_parallel_residual": false, | |
| "vocab_size": 50432 | |
| } | |