Instructions to use HenryJJ/llama3-8b-cqia with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use HenryJJ/llama3-8b-cqia with Transformers:

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

pipe = pipeline("text-generation", model="HenryJJ/llama3-8b-cqia")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("HenryJJ/llama3-8b-cqia")
model = AutoModelForMultimodalLM.from_pretrained("HenryJJ/llama3-8b-cqia")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use HenryJJ/llama3-8b-cqia with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "HenryJJ/llama3-8b-cqia"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HenryJJ/llama3-8b-cqia",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/HenryJJ/llama3-8b-cqia

SGLang

How to use HenryJJ/llama3-8b-cqia 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 "HenryJJ/llama3-8b-cqia" \
    --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": "HenryJJ/llama3-8b-cqia",
		"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 "HenryJJ/llama3-8b-cqia" \
        --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": "HenryJJ/llama3-8b-cqia",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use HenryJJ/llama3-8b-cqia with Docker Model Runner:
```
docker model run hf.co/HenryJJ/llama3-8b-cqia
```

HenryJJ commited on Apr 27, 2024

Commit

22ed900

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Update README.md

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@@ -4,11 +4,11 @@ datasets:
 - m-a-p/COIG-CQIA
 ---
-# llama3-8B-cqia
 [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
-SFT with m-a-p/COIG-CQIA. 2 epoch qlora. Code under [https://huggingface.co/HenryJJ/llama3-8B-lima/blob/main/config/llama3-cqia.yml](https://huggingface.co/HenryJJ/llama3-8B-lima/blob/main/config/llama3-llama3-cqia.yml).
 # Model Details
 * **Trained by**: trained by HenryJJ.

 - m-a-p/COIG-CQIA
 ---
+# llama3-8b-cqia
 [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+SFT with m-a-p/COIG-CQIA. 2 epoch qlora. Code under [https://huggingface.co/HenryJJ/llama3-8b-lima/blob/main/config/llama3-cqia.yml](https://huggingface.co/HenryJJ/llama3-8b-lima/blob/main/config/llama3-llama3-cqia.yml).
 # Model Details
 * **Trained by**: trained by HenryJJ.