Instructions to use lewiswu1209/Winnie with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lewiswu1209/Winnie with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="lewiswu1209/Winnie")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("lewiswu1209/Winnie") model = AutoModelForCausalLM.from_pretrained("lewiswu1209/Winnie") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use lewiswu1209/Winnie with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lewiswu1209/Winnie" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lewiswu1209/Winnie", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/lewiswu1209/Winnie
- SGLang
How to use lewiswu1209/Winnie 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 "lewiswu1209/Winnie" \ --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": "lewiswu1209/Winnie", "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 "lewiswu1209/Winnie" \ --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": "lewiswu1209/Winnie", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use lewiswu1209/Winnie with Docker Model Runner:
docker model run hf.co/lewiswu1209/Winnie
Winnie
Winnie是基于cambridgeltl/simctg_lccc_dialogue训练的
我修改了vocab.txt, 新增了[NAME][NICK][GENDER][YEAROFBIRTH][MONTHOFBIRTH][DAYOFBIRTH][ZODIAC][AGE]几个special_token,然后搞了些类似
你是谁?
我是[NAME]。
你叫什么?
我叫[NAME]。
你多大啦?
我[AGE]岁了。
的语料。
第一次训练的时候起名叫Vicky,然后把Vicky的脑子训瓦特了,只能摸索新的办法了。 后来利用了50W闲聊语料搭配新增的语料按照大约19:1的比例进行训练,感觉效果还可以。
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