Instructions to use luffycodes/vicuna-class-shishya-13b-ep3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use luffycodes/vicuna-class-shishya-13b-ep3 with Transformers:

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

pipe = pipeline("text-generation", model="luffycodes/vicuna-class-shishya-13b-ep3")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("luffycodes/vicuna-class-shishya-13b-ep3")
model = AutoModelForCausalLM.from_pretrained("luffycodes/vicuna-class-shishya-13b-ep3", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use luffycodes/vicuna-class-shishya-13b-ep3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "luffycodes/vicuna-class-shishya-13b-ep3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "luffycodes/vicuna-class-shishya-13b-ep3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/luffycodes/vicuna-class-shishya-13b-ep3

SGLang

How to use luffycodes/vicuna-class-shishya-13b-ep3 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 "luffycodes/vicuna-class-shishya-13b-ep3" \
    --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": "luffycodes/vicuna-class-shishya-13b-ep3",
		"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 "luffycodes/vicuna-class-shishya-13b-ep3" \
        --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": "luffycodes/vicuna-class-shishya-13b-ep3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use luffycodes/vicuna-class-shishya-13b-ep3 with Docker Model Runner:
```
docker model run hf.co/luffycodes/vicuna-class-shishya-13b-ep3
```

luffycodes commited on Dec 21, 2023

Commit

493312a

1 Parent(s): 0534895

Create README.md

Browse files

Files changed (1) hide show

README.md +16 -0

README.md ADDED Viewed

	@@ -0,0 +1,16 @@

+---
+license: llama2
+---
+If you use this work, please cite:
+CLASS Meet SPOCK: An Education Tutoring Chatbot based on Learning Science Principles
+https://arxiv.org/abs/2305.13272
+```
+@misc{sonkar2023class,
+      title={CLASS Meet SPOCK: An Education Tutoring Chatbot based on Learning Science Principles},
+      author={Shashank Sonkar and Lucy Liu and Debshila Basu Mallick and Richard G. Baraniuk},
+      year={2023},
+      eprint={2305.13272},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```