Instructions to use yujiepan/opt-tiny-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yujiepan/opt-tiny-random with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="yujiepan/opt-tiny-random")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("yujiepan/opt-tiny-random") model = AutoModelForCausalLM.from_pretrained("yujiepan/opt-tiny-random") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use yujiepan/opt-tiny-random with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "yujiepan/opt-tiny-random" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "yujiepan/opt-tiny-random", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/yujiepan/opt-tiny-random
- SGLang
How to use yujiepan/opt-tiny-random 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 "yujiepan/opt-tiny-random" \ --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": "yujiepan/opt-tiny-random", "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 "yujiepan/opt-tiny-random" \ --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": "yujiepan/opt-tiny-random", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use yujiepan/opt-tiny-random with Docker Model Runner:
docker model run hf.co/yujiepan/opt-tiny-random
metadata
pipeline_tag: text-generation
inference: true
widget:
- text: Hello!
example_title: Hello world
group: Python
library_name: transformers
This model is randomly initialized, using the config from facebook/opt-30b but with smaller size. Note the model is in float16.
Codes:
import torch
import transformers
import os
from optimum.intel.openvino import OVModelForCausalLM
save_path = '/tmp/yujiepan/opt-tiny-random'
repo_id = 'yujiepan/opt-tiny-random'
config = transformers.AutoConfig.from_pretrained('facebook/opt-30b')
config.ffn_dim = 32
config.hidden_size = 8
config.num_attention_heads = 2
config.num_hidden_layers = 2
config.word_embed_proj_dim = 8
model = transformers.AutoModelForCausalLM.from_config(config, torch_dtype=torch.float16)
model = model.half()
model.save_pretrained(save_path)
tokenizer = transformers.AutoTokenizer.from_pretrained('facebook/opt-30b')
tokenizer.save_pretrained(save_path)
ovmodel = OVModelForCausalLM.from_pretrained(save_path, export=True)
ovmodel = ovmodel.half()
ovmodel.save_pretrained(save_path)
os.system(f'ls -alh {save_path}')
from huggingface_hub import create_repo, upload_folder
create_repo(repo_id, exist_ok=True)
upload_folder(repo_id=repo_id, folder_path=save_path)