Instructions to use IDEA-CCNL/Ziya2-13B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IDEA-CCNL/Ziya2-13B-Base with Transformers:

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

pipe = pipeline("text-generation", model="IDEA-CCNL/Ziya2-13B-Base")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("IDEA-CCNL/Ziya2-13B-Base")
model = AutoModelForCausalLM.from_pretrained("IDEA-CCNL/Ziya2-13B-Base", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use IDEA-CCNL/Ziya2-13B-Base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "IDEA-CCNL/Ziya2-13B-Base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IDEA-CCNL/Ziya2-13B-Base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/IDEA-CCNL/Ziya2-13B-Base

SGLang

How to use IDEA-CCNL/Ziya2-13B-Base 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 "IDEA-CCNL/Ziya2-13B-Base" \
    --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": "IDEA-CCNL/Ziya2-13B-Base",
		"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 "IDEA-CCNL/Ziya2-13B-Base" \
        --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": "IDEA-CCNL/Ziya2-13B-Base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use IDEA-CCNL/Ziya2-13B-Base with Docker Model Runner:
```
docker model run hf.co/IDEA-CCNL/Ziya2-13B-Base
```

Zimix commited on Mar 29, 2024

Commit

91c5a0b

verified ·

1 Parent(s): 2ac99e7

Update README.md

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README.md +2 -9

README.md CHANGED Viewed

@@ -1,26 +1,19 @@
 ---
 tasks:
 - text-generation
 model_type:
 - gpt
 - llama
 domain:
 - nlp
 language:
 - en
 - zh
 - cn
 tags:
 - transformer
 - 封神榜
 ---
 # Ziya2-13B-Base
@@ -124,4 +117,4 @@ You can also cite our [website](https://github.com/IDEA-CCNL/Fengshenbang-LM/):
       archivePrefix={arXiv},
       primaryClass={cs.CL}
 }
-```

 ---
 tasks:
 - text-generation
 model_type:
 - gpt
 - llama
 domain:
 - nlp
 language:
 - en
 - zh
 - cn
 tags:
 - transformer
 - 封神榜
+license: apache-2.0
 ---
 # Ziya2-13B-Base
       archivePrefix={arXiv},
       primaryClass={cs.CL}
 }
+```