Instructions to use Salesforce/xgen-7b-8k-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Salesforce/xgen-7b-8k-base with Transformers:

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

pipe = pipeline("text-generation", model="Salesforce/xgen-7b-8k-base")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Salesforce/xgen-7b-8k-base")
model = AutoModelForCausalLM.from_pretrained("Salesforce/xgen-7b-8k-base")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Salesforce/xgen-7b-8k-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-8k-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-8k-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Salesforce/xgen-7b-8k-base

SGLang

How to use Salesforce/xgen-7b-8k-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-8k-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-8k-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-8k-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-8k-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Salesforce/xgen-7b-8k-base with Docker Model Runner:
```
docker model run hf.co/Salesforce/xgen-7b-8k-base
```

tokenization mismatch

#25

by ehartford - opened Jul 18, 2023

Discussion

ehartford

Jul 18, 2023

I'm using fastchat to finetune, and I get errors like this:

WARNING: tokenization mismatch: 381 vs. 382. (ignored)
WARNING: tokenization mismatch: 411 vs. 412. (ignored)
WARNING: tokenization mismatch: 250 vs. 251. (ignored)
WARNING: tokenization mismatch: 117 vs. 119. (ignored)
WARNING: tokenization mismatch: 508 vs. 510. (ignored)
WARNING: tokenization mismatch: 511 vs. 512. (ignored)
WARNING: tokenization mismatch: 713 vs. 714. (ignored)
WARNING: tokenization mismatch: 253 vs. 255. (ignored)
WARNING: tokenization mismatch: 461 vs. 463. (ignored)
WARNING: tokenization mismatch: 233 vs. 234. (ignored)
WARNING: tokenization mismatch: 235 vs. 236. (ignored)
WARNING: tokenization mismatch: 2281 vs. 2282. (ignored)
WARNING: tokenization mismatch: 276 vs. 277. (ignored)
WARNING: tokenization mismatch: 907 vs. 908. (ignored)
WARNING: tokenization mismatch: 171 vs. 172. (ignored)
WARNING: tokenization mismatch: 360 vs. 361. (ignored)

Any idea?

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment