Instructions to use Salesforce/codegen25-7b-multi_P with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Salesforce/codegen25-7b-multi_P with Transformers:

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

pipe = pipeline("text-generation", model="Salesforce/codegen25-7b-multi_P")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen25-7b-multi_P")
model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen25-7b-multi_P")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Salesforce/codegen25-7b-multi_P with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Salesforce/codegen25-7b-multi_P"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Salesforce/codegen25-7b-multi_P",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Salesforce/codegen25-7b-multi_P

SGLang

How to use Salesforce/codegen25-7b-multi_P 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 "Salesforce/codegen25-7b-multi_P" \
    --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": "Salesforce/codegen25-7b-multi_P",
		"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 "Salesforce/codegen25-7b-multi_P" \
        --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": "Salesforce/codegen25-7b-multi_P",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Salesforce/codegen25-7b-multi_P with Docker Model Runner:
```
docker model run hf.co/Salesforce/codegen25-7b-multi_P
```

Jaskirat Singh commited on Jul 7, 2023

Commit

bc26f7e

1 Parent(s): 85a4c61

Fixed model name in example

Browse files

Files changed (1) hide show

README.md +1 -1

README.md CHANGED Viewed

@@ -75,7 +75,7 @@ The final snippet looks as follows:
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen25-7b-multi", trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen2k-7b-multi")
 def format(prefix, suffix):

 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 tokenizer = AutoTokenizer.from_pretrained("Salesforce/codegen25-7b-multi", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("Salesforce/codegen25-7b-multi")
 def format(prefix, suffix):