Instructions to use ocolegro/opt-1.3b-50_epoch_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ocolegro/opt-1.3b-50_epoch_v2 with Transformers:

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

pipe = pipeline("text-generation", model="ocolegro/opt-1.3b-50_epoch_v2")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ocolegro/opt-1.3b-50_epoch_v2")
model = AutoModelForCausalLM.from_pretrained("ocolegro/opt-1.3b-50_epoch_v2", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ocolegro/opt-1.3b-50_epoch_v2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ocolegro/opt-1.3b-50_epoch_v2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ocolegro/opt-1.3b-50_epoch_v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ocolegro/opt-1.3b-50_epoch_v2

SGLang

How to use ocolegro/opt-1.3b-50_epoch_v2 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 "ocolegro/opt-1.3b-50_epoch_v2" \
    --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": "ocolegro/opt-1.3b-50_epoch_v2",
		"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 "ocolegro/opt-1.3b-50_epoch_v2" \
        --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": "ocolegro/opt-1.3b-50_epoch_v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ocolegro/opt-1.3b-50_epoch_v2 with Docker Model Runner:
```
docker model run hf.co/ocolegro/opt-1.3b-50_epoch_v2
```

Training QA

by robinzixuan - opened Aug 17, 2024

Discussion

robinzixuan

Aug 17, 2024

How much training steps it takes to and what the data use in training.

robinzixuan changed discussion title from How much training steps it takes to and what the data use in training. to Training QA Aug 17, 2024

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