Instructions to use explosion-testing/mpt-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use explosion-testing/mpt-test with Transformers:

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

pipe = pipeline("text-generation", model="explosion-testing/mpt-test", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("explosion-testing/mpt-test", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("explosion-testing/mpt-test", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use explosion-testing/mpt-test with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/explosion-testing/mpt-test

SGLang

How to use explosion-testing/mpt-test 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 "explosion-testing/mpt-test" \
    --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": "explosion-testing/mpt-test",
		"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 "explosion-testing/mpt-test" \
        --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": "explosion-testing/mpt-test",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use explosion-testing/mpt-test with Docker Model Runner:
```
docker model run hf.co/explosion-testing/mpt-test
```

mpt-test

File size: 770 Bytes

{
  "architectures": [
    "MptForCausalLM"
  ],
  "attn_config": {
    "attn_impl": "torch"
  },
  "auto_map": {
    "AutoConfig": "configuration_mpt.MPTConfig",
    "AutoModelForCausalLM": "modeling_mpt.MPTForCausalLM"
  },
  "d_model": 32,
  "emb_pdrop": 0.0,
  "embedding_fraction": 1.0,
  "expansion_ratio": 4,
  "init_device": "cpu",
  "initializer_range": 0.02,
  "layer_norm_epsilon": 1e-05,
  "learned_pos_emb": true,
  "logit_scale": null,
  "max_seq_len": 2048,
  "model_type": "mpt",
  "n_heads": 4,
  "n_layers": 5,
  "no_bias": true,
  "norm_type": "low_precision_layernorm",
  "num_key_value_heads": 2,
  "resid_pdrop": 0.0,
  "torch_dtype": "float32",
  "transformers_version": "4.32.0.dev0",
  "use_cache": false,
  "verbose": 0,
  "vocab_size": 1024
}