Instructions to use yujiepan/mpt-tiny-random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use yujiepan/mpt-tiny-random with Transformers:

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

pipe = pipeline("text-generation", model="yujiepan/mpt-tiny-random", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("yujiepan/mpt-tiny-random", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("yujiepan/mpt-tiny-random", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use yujiepan/mpt-tiny-random with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/yujiepan/mpt-tiny-random

SGLang

How to use yujiepan/mpt-tiny-random 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 "yujiepan/mpt-tiny-random" \
    --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": "yujiepan/mpt-tiny-random",
		"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 "yujiepan/mpt-tiny-random" \
        --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": "yujiepan/mpt-tiny-random",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use yujiepan/mpt-tiny-random with Docker Model Runner:
```
docker model run hf.co/yujiepan/mpt-tiny-random
```

yujiepan commited on Oct 29, 2023

Commit

7bbe5a6

1 Parent(s): 1b510f2

Update README.md

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Files changed (1) hide show

README.md +4 -3

README.md CHANGED Viewed

@@ -39,9 +39,10 @@ model.save_pretrained(save_path)
 tokenizer = transformers.AutoTokenizer.from_pretrained(model_id)
 tokenizer.save_pretrained(save_path)
-# from optimum.intel.openvino import OVModelForCausalLM
-# ovmodel = OVModelForCausalLM.from_pretrained(save_path, export=True)
-# ovmodel.save_pretrained(save_path)
 os.system(f'ls -alh {save_path}')
 create_repo(repo_id, exist_ok=True)

 tokenizer = transformers.AutoTokenizer.from_pretrained(model_id)
 tokenizer.save_pretrained(save_path)
+from optimum.intel.openvino import OVModelForCausalLM
+ovmodel = OVModelForCausalLM.from_pretrained(save_path, export=True)
+ovmodel = ovmodel.half()
+ovmodel.save_pretrained(save_path)
 os.system(f'ls -alh {save_path}')
 create_repo(repo_id, exist_ok=True)