Instructions to use FreedomIntelligence/AceGPT-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FreedomIntelligence/AceGPT-7B with Transformers:

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

pipe = pipeline("text-generation", model="FreedomIntelligence/AceGPT-7B")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("FreedomIntelligence/AceGPT-7B")
model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/AceGPT-7B", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use FreedomIntelligence/AceGPT-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FreedomIntelligence/AceGPT-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FreedomIntelligence/AceGPT-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/FreedomIntelligence/AceGPT-7B

SGLang

How to use FreedomIntelligence/AceGPT-7B 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 "FreedomIntelligence/AceGPT-7B" \
    --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": "FreedomIntelligence/AceGPT-7B",
		"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 "FreedomIntelligence/AceGPT-7B" \
        --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": "FreedomIntelligence/AceGPT-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use FreedomIntelligence/AceGPT-7B with Docker Model Runner:
```
docker model run hf.co/FreedomIntelligence/AceGPT-7B
```

sxn6144 commited on Sep 18, 2023

Commit

2feec51

1 Parent(s): 0281286

Update README.md

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@@ -4,5 +4,13 @@ language:
 - ar
 ---
 # AceGPT
-AceGPT is a fully fine-tuned generative text model collection based on LlaMA2, particularly in the Arabic language domain.
-This is the repository for the 7B pretrained model。

 - ar
 ---
 # AceGPT
+AceGPT is a fully fine-tuned generative text model collection based on LlaMA2, particularly in the
+Arabic language domain. This is the repository for the 7B pretrained model.
+# Model Details
+We have released the AceGPT family of large language models, which is a collection of fully fine-tuned
+generative text models based on LlaMA2, ranging from 7B to 13B parameters. Our models include two main
+categories: AceGPT and AceGPT-chat. AceGPT-chat is an optimized version specifically designed for dialogue
+applications. It is worth mentioning that our models have demonstrated superior performance compared
+to all currently available open-source Arabic dialogue models in multiple benchmark tests. Furthermore,
+in our human evaluations, our models have shown comparable satisfaction levels to some closed-source models,
+such as ChatGPT, in the Arabic language.