Instructions to use normalcomputing/extended-mind-mpt-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use normalcomputing/extended-mind-mpt-7b with Transformers:

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

pipe = pipeline("text-generation", model="normalcomputing/extended-mind-mpt-7b", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("normalcomputing/extended-mind-mpt-7b", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use normalcomputing/extended-mind-mpt-7b with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/normalcomputing/extended-mind-mpt-7b

SGLang

How to use normalcomputing/extended-mind-mpt-7b 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 "normalcomputing/extended-mind-mpt-7b" \
    --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": "normalcomputing/extended-mind-mpt-7b",
		"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 "normalcomputing/extended-mind-mpt-7b" \
        --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": "normalcomputing/extended-mind-mpt-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use normalcomputing/extended-mind-mpt-7b with Docker Model Runner:
```
docker model run hf.co/normalcomputing/extended-mind-mpt-7b
```

phoebeklett commited on Oct 31, 2023

Commit

1d73c7c

1 Parent(s): ca22bee

Create README.md

Browse files

Files changed (1) hide show

README.md +30 -0

README.md ADDED Viewed

	@@ -0,0 +1,30 @@

+---
+# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
+# Doc / guide: https://huggingface.co/docs/hub/model-cards
+{}
+---
+# Model Card for Extended-Mind-MPT-7b
+<!-- Provide a quick summary of what the model is/does. -->
+Extended Mind MPT-7b, as described in [Supersizing Transformers](https://blog.normalcomputing.ai/posts/2023-09-12-supersizing-transformers/supersizing-transformers.html).
+### Model Description
+<!-- Provide a longer summary of what this model is. -->
+This model implements active externalism for MPT's 7b model. The model weights have not been edited. Original architecture and code by Mosaic ML.
+For more details on active externalism, check out our [blog](https://blog.normalcomputing.ai/posts/2023-09-12-supersizing-transformers/supersizing-transformers.html)!
+- **Developed by:** [Normal Computing](https://huggingface.co/normalcomputing), Adapted from [Mosacic ML](https://huggingface.co/mosaicml)
+- **License:** Apache 2.0
+## Limitations
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+This model is part of ongoing research at Normal Computing.