Instructions to use kaitchup/OPT-1.3B-SFT-DSChatLoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use kaitchup/OPT-1.3B-SFT-DSChatLoRA with Transformers:

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

pipe = pipeline("text-generation", model="kaitchup/OPT-1.3B-SFT-DSChatLoRA")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("kaitchup/OPT-1.3B-SFT-DSChatLoRA")
model = AutoModelForCausalLM.from_pretrained("kaitchup/OPT-1.3B-SFT-DSChatLoRA")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use kaitchup/OPT-1.3B-SFT-DSChatLoRA with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "kaitchup/OPT-1.3B-SFT-DSChatLoRA"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "kaitchup/OPT-1.3B-SFT-DSChatLoRA",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/kaitchup/OPT-1.3B-SFT-DSChatLoRA

SGLang

How to use kaitchup/OPT-1.3B-SFT-DSChatLoRA 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 "kaitchup/OPT-1.3B-SFT-DSChatLoRA" \
    --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": "kaitchup/OPT-1.3B-SFT-DSChatLoRA",
		"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 "kaitchup/OPT-1.3B-SFT-DSChatLoRA" \
        --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": "kaitchup/OPT-1.3B-SFT-DSChatLoRA",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use kaitchup/OPT-1.3B-SFT-DSChatLoRA with Docker Model Runner:
```
docker model run hf.co/kaitchup/OPT-1.3B-SFT-DSChatLoRA
```

Model Card for Model ID

This a model is a fine-tuned with SFT using DeepSpeed Chat. It is based on OPT-1.3M.B

Model Details

Model Description

Developed by: The Kaitchup
Model type: Causal
Language(s) (NLP): English
License: cc-by-nc-sa-4.0
Finetuned from model: facebook/opt-1.3b

Model Sources

The model has been trained with the procedure described in this article:

Train Instruct LLMs On Your GPU with DeepSpeed Chat — Step #1: Supervised Fine-tuning

Downloads last month: 7

Safetensors

Model size

1B params

Tensor type

F16

kaitchup
/

OPT-1.3B-SFT-DSChatLoRA

Model Card for Model ID

Model Details

Model Description

Model Sources

Datasets used to train kaitchup/OPT-1.3B-SFT-DSChatLoRA