Instructions to use Salesforce/xgen-7b-4k-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Salesforce/xgen-7b-4k-base with Transformers:

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

pipe = pipeline("text-generation", model="Salesforce/xgen-7b-4k-base")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Salesforce/xgen-7b-4k-base")
model = AutoModelForCausalLM.from_pretrained("Salesforce/xgen-7b-4k-base")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Salesforce/xgen-7b-4k-base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Salesforce/xgen-7b-4k-base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Salesforce/xgen-7b-4k-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Salesforce/xgen-7b-4k-base

SGLang

How to use Salesforce/xgen-7b-4k-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 "Salesforce/xgen-7b-4k-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": "Salesforce/xgen-7b-4k-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 "Salesforce/xgen-7b-4k-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": "Salesforce/xgen-7b-4k-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Salesforce/xgen-7b-4k-base with Docker Model Runner:
```
docker model run hf.co/Salesforce/xgen-7b-4k-base
```

tianxie-sf commited on Jul 7, 2023

Commit

09afc93

1 Parent(s): 9936980

fix issue in get vocab

Browse files

Files changed (1) hide show

tokenization_xgen.py +1 -1

tokenization_xgen.py CHANGED Viewed

@@ -139,7 +139,7 @@ class XgenTokenizer(PreTrainedTokenizer):
     def get_vocab(self):
         """Returns vocab as a dict"""
-        vocab = {self._convert_id_to_token(i): i for i in range(self.vocab_size)}
         return vocab
     def _tokenize(self, text, **kwargs):

     def get_vocab(self):
         """Returns vocab as a dict"""
+        vocab = {self.encoder.decode_single_token_bytes(i): i for i in range(self.vocab_size)}
         return vocab
     def _tokenize(self, text, **kwargs):