Instructions to use None1145/Llama-3-8B-Theresa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use None1145/Llama-3-8B-Theresa with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="None1145/Llama-3-8B-Theresa")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("None1145/Llama-3-8B-Theresa", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use None1145/Llama-3-8B-Theresa with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "None1145/Llama-3-8B-Theresa"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "None1145/Llama-3-8B-Theresa",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/None1145/Llama-3-8B-Theresa

SGLang

How to use None1145/Llama-3-8B-Theresa 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 "None1145/Llama-3-8B-Theresa" \
    --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": "None1145/Llama-3-8B-Theresa",
		"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 "None1145/Llama-3-8B-Theresa" \
        --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": "None1145/Llama-3-8B-Theresa",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use None1145/Llama-3-8B-Theresa with Docker Model Runner:
```
docker model run hf.co/None1145/Llama-3-8B-Theresa
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Model Introduction

These models are based on the text training of Theresa from Arknights

Chat

import transformers
import torch

ver = "ver0.2"
model_id = "None1145/Llama-3-8B-Theresa/{ver}"

pipeline = transformers.pipeline(
    "text-generation", model=model_id, model_kwargs={"torch_dtype": torch.bfloat16}, device_map="auto"
)
pipeline("你好")

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Dataset used to train None1145/Llama-3-8B-Theresa