Instructions to use crumb/test-00-switchllama-i3b-f10b-e4-init with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use crumb/test-00-switchllama-i3b-f10b-e4-init with Transformers:

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

pipe = pipeline("text-generation", model="crumb/test-00-switchllama-i3b-f10b-e4-init", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("crumb/test-00-switchllama-i3b-f10b-e4-init", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use crumb/test-00-switchllama-i3b-f10b-e4-init with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "crumb/test-00-switchllama-i3b-f10b-e4-init"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "crumb/test-00-switchllama-i3b-f10b-e4-init",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/crumb/test-00-switchllama-i3b-f10b-e4-init

SGLang

How to use crumb/test-00-switchllama-i3b-f10b-e4-init 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 "crumb/test-00-switchllama-i3b-f10b-e4-init" \
    --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": "crumb/test-00-switchllama-i3b-f10b-e4-init",
		"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 "crumb/test-00-switchllama-i3b-f10b-e4-init" \
        --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": "crumb/test-00-switchllama-i3b-f10b-e4-init",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use crumb/test-00-switchllama-i3b-f10b-e4-init with Docker Model Runner:
```
docker model run hf.co/crumb/test-00-switchllama-i3b-f10b-e4-init
```

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Check out the documentation for more information.

this is the initial model warmstarted from openllama 3b v2 with the expert layers copied from models trained with lora on only the mlp layers, if you can find the problem with the modeling code i will send you a picture of my cat

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Collection including crumb/test-00-switchllama-i3b-f10b-e4-init

MoLora-v2

Collection

First Prototype of the second iteration of MoLora utilizing mixture of expert techniques applied to the Llama2 model. • 5 items • Updated Sep 9, 2023 • 2