Instructions to use shafire/SpectraMind3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use shafire/SpectraMind3 with Transformers:

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

pipe = pipeline("text-generation", model="shafire/SpectraMind3")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("shafire/SpectraMind3", device_map="auto")

PEFT
How to use shafire/SpectraMind3 with PEFT:
```
Task type is invalid.
```
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use shafire/SpectraMind3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "shafire/SpectraMind3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "shafire/SpectraMind3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/shafire/SpectraMind3

SGLang

How to use shafire/SpectraMind3 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 "shafire/SpectraMind3" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "shafire/SpectraMind3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "shafire/SpectraMind3" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "shafire/SpectraMind3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use shafire/SpectraMind3 with Docker Model Runner:
```
docker model run hf.co/shafire/SpectraMind3
```

shafire commited on Nov 16, 2024

Commit

f21f7c4

verified ·

1 Parent(s): 1ef2be7

Upload folder using huggingface_hub

Browse files

Files changed (1) hide show

runs/Nov16_03-27-42_r-shafire-spectramind3-2-tnul1bb8-1d75b-15f5r/events.out.tfevents.1731727748.r-shafire-spectramind3-2-tnul1bb8-1d75b-15f5r.221.0 +2 -2

runs/Nov16_03-27-42_r-shafire-spectramind3-2-tnul1bb8-1d75b-15f5r/events.out.tfevents.1731727748.r-shafire-spectramind3-2-tnul1bb8-1d75b-15f5r.221.0 CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8405e7d8944d51943af429867c8aad5c34b635bd900265adf5acedcb8a9501e5
-size 6988

 version https://git-lfs.github.com/spec/v1
+oid sha256:856a29e700b477251b168a605d88dcfad98226bc15fa85fd59d59a35feeafaef
+size 7828