Instructions to use kuotient/Llama-3-8B-Instruct-vector-diff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use kuotient/Llama-3-8B-Instruct-vector-diff with Transformers:

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

pipe = pipeline("text-generation", model="kuotient/Llama-3-8B-Instruct-vector-diff")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("kuotient/Llama-3-8B-Instruct-vector-diff")
model = AutoModelForCausalLM.from_pretrained("kuotient/Llama-3-8B-Instruct-vector-diff")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use kuotient/Llama-3-8B-Instruct-vector-diff with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "kuotient/Llama-3-8B-Instruct-vector-diff"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "kuotient/Llama-3-8B-Instruct-vector-diff",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/kuotient/Llama-3-8B-Instruct-vector-diff

SGLang

How to use kuotient/Llama-3-8B-Instruct-vector-diff 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 "kuotient/Llama-3-8B-Instruct-vector-diff" \
    --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": "kuotient/Llama-3-8B-Instruct-vector-diff",
		"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 "kuotient/Llama-3-8B-Instruct-vector-diff" \
        --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": "kuotient/Llama-3-8B-Instruct-vector-diff",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use kuotient/Llama-3-8B-Instruct-vector-diff with Docker Model Runner:
```
docker model run hf.co/kuotient/Llama-3-8B-Instruct-vector-diff
```

kuotient commited on May 24, 2024

Commit

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@@ -4,7 +4,7 @@ license: other
 # Llama-3 chat vector
 - Update 0426: A small problem with the deployment of the model 'Llama-3-Seagull-Evo-8B', but we hope to have it back in good time!
-- Update 0526: Check our newest EMM model, [Alpha-Ko-8B-Instruct](allganize/Llama-3-Alpha-Ko-8B-Instruct)
 This is 'modelified' version of _chat vector_ from the paper [Chat Vector: A Simple Approach to Equip LLMs with Instruction Following and Model Alignment in New Languages](https://arxiv.org/abs/2310.04799). So this is not a model, its just weight diff, just for ease to use myself(or you too)!

 # Llama-3 chat vector
 - Update 0426: A small problem with the deployment of the model 'Llama-3-Seagull-Evo-8B', but we hope to have it back in good time!
+- Update 0526: Check our newest EMM model, [Alpha-Ko-8B-Instruct](https://huggingface.co/allganize/Llama-3-Alpha-Ko-8B-Instruct)
 This is 'modelified' version of _chat vector_ from the paper [Chat Vector: A Simple Approach to Equip LLMs with Instruction Following and Model Alignment in New Languages](https://arxiv.org/abs/2310.04799). So this is not a model, its just weight diff, just for ease to use myself(or you too)!