Instructions to use zai-org/agentlm-13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zai-org/agentlm-13b with Transformers:

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

pipe = pipeline("text-generation", model="zai-org/agentlm-13b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("zai-org/agentlm-13b")
model = AutoModelForCausalLM.from_pretrained("zai-org/agentlm-13b")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use zai-org/agentlm-13b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zai-org/agentlm-13b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zai-org/agentlm-13b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/zai-org/agentlm-13b

SGLang

How to use zai-org/agentlm-13b 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 "zai-org/agentlm-13b" \
    --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": "zai-org/agentlm-13b",
		"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 "zai-org/agentlm-13b" \
        --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": "zai-org/agentlm-13b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use zai-org/agentlm-13b with Docker Model Runner:
```
docker model run hf.co/zai-org/agentlm-13b
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

AgentLM-13B

🤗 [Dataset] • 💻 [Github Repo] • 📌 [Project Page] • 📃 [Paper]

AgentTuning represents the very first attempt to instruction-tune LLMs using interaction trajectories across multiple agent tasks. Evaluation results indicate that AgentTuning enables the agent capabilities of LLMs with robust generalization on unseen agent tasks while remaining good on general language abilities. We have open-sourced the AgentInstruct dataset and AgentLM.

Models

AgentLM models are produced by mixed training on AgentInstruct dataset and ShareGPT dataset from Llama-2-chat models.

The models follow the conversation format of Llama-2-chat, with system prompt fixed as

You are a helpful, respectful and honest assistant.

7B, 13B, and 70B models are available on Huggingface model hub.

Model	Huggingface Repo
AgentLM-7B	🤗Huggingface Repo
AgentLM-13B	🤗Huggingface Repo
AgentLM-70B	🤗Huggingface Repo

Citation

If you find our work useful, please consider citing AgentTuning:

@misc{zeng2023agenttuning,
      title={AgentTuning: Enabling Generalized Agent Abilities for LLMs}, 
      author={Aohan Zeng and Mingdao Liu and Rui Lu and Bowen Wang and Xiao Liu and Yuxiao Dong and Jie Tang},
      year={2023},
      eprint={2310.12823},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

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Safetensors

Model size

13B params

Tensor type

F32

F16

Model tree for zai-org/agentlm-13b

Quantizations

3 models

Dataset used to train zai-org/agentlm-13b

Spaces using zai-org/agentlm-13b 2

Paper for zai-org/agentlm-13b

AgentTuning: Enabling Generalized Agent Abilities for LLMs

Paper • 2310.12823 • Published Oct 19, 2023 • 36