Instructions to use TigerResearch/SoftTiger-70b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TigerResearch/SoftTiger-70b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TigerResearch/SoftTiger-70b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TigerResearch/SoftTiger-70b") model = AutoModelForCausalLM.from_pretrained("TigerResearch/SoftTiger-70b") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use TigerResearch/SoftTiger-70b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TigerResearch/SoftTiger-70b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TigerResearch/SoftTiger-70b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TigerResearch/SoftTiger-70b
- SGLang
How to use TigerResearch/SoftTiger-70b 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 "TigerResearch/SoftTiger-70b" \ --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": "TigerResearch/SoftTiger-70b", "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 "TigerResearch/SoftTiger-70b" \ --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": "TigerResearch/SoftTiger-70b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TigerResearch/SoftTiger-70b with Docker Model Runner:
docker model run hf.co/TigerResearch/SoftTiger-70b
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license: apache-2.0
language:
- zh
- en
---
<div style="width: 100%;">
<p align="center">
<img src="http://x-pai.algolet.com/bot/img/logo_core.png" alt="TigerBot" width="20%" style="display: inline-block;"></img>
<img src="https://www.sofya.ai/logo.svg" alt="Sofya" width="20%" style="display: inline-block;"></img>
</p>
</div>
<p align="center">
<font face="黑体" size=5"> A cutting-edge foundation for your very own LLM. </font>
</p>
<p align="center">
💻<a href="https://github.com/TigerResearch/TigerBot" target="_blank">Github</a> • 🌐 <a href="https://tigerbot.com/" target="_blank">TigerBot</a> • 🤗 <a href="https://huggingface.co/TigerResearch" target="_blank">Hugging Face</a>
</p>
# 快速开始
- 方法1,通过transformers使用
- 下载 TigerBot Repo
```shell
git clone https://github.com/TigerResearch/TigerBot.git
```
- 启动infer代码
```shell
python infer.py --model_path TigerResearch/SoftTiger-70b
```
- 方法2:
- 下载 TigerBot Repo
```shell
git clone https://github.com/TigerResearch/TigerBot.git
```
- 安装git lfs: `git lfs install`
- 通过huggingface下载权重
```shell
git clone https://huggingface.co/TigerResearch/SoftTiger-70b
```
- 启动infer代码
```shell
python infer.py --model_path SoftTiger-70b
```
------
# Quick Start
- Method 1, use through transformers
- Clone TigerBot Repo
```shell
git clone https://github.com/TigerResearch/TigerBot.git
```
- Run infer script
```shell
python infer.py --model_path TigerResearch/SoftTiger-70b
```
- Method 2:
- Clone TigerBot Repo
```shell
git clone https://github.com/TigerResearch/TigerBot.git
```
- install git lfs: `git lfs install`
- Download weights from huggingface
```shell
git clone https://huggingface.co/TigerResearch/SoftTiger-70b
```
- Run infer script
```shell
python infer.py --model_path SoftTiger-70b
``` |