Instructions to use lambda/pythia-1.4b-deduped-synthetic-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use lambda/pythia-1.4b-deduped-synthetic-instruct with Transformers:

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

pipe = pipeline("text-generation", model="lambda/pythia-1.4b-deduped-synthetic-instruct")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("lambda/pythia-1.4b-deduped-synthetic-instruct")
model = AutoModelForCausalLM.from_pretrained("lambda/pythia-1.4b-deduped-synthetic-instruct")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use lambda/pythia-1.4b-deduped-synthetic-instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "lambda/pythia-1.4b-deduped-synthetic-instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "lambda/pythia-1.4b-deduped-synthetic-instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/lambda/pythia-1.4b-deduped-synthetic-instruct

SGLang

How to use lambda/pythia-1.4b-deduped-synthetic-instruct 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 "lambda/pythia-1.4b-deduped-synthetic-instruct" \
    --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": "lambda/pythia-1.4b-deduped-synthetic-instruct",
		"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 "lambda/pythia-1.4b-deduped-synthetic-instruct" \
        --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": "lambda/pythia-1.4b-deduped-synthetic-instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use lambda/pythia-1.4b-deduped-synthetic-instruct with Docker Model Runner:
```
docker model run hf.co/lambda/pythia-1.4b-deduped-synthetic-instruct
```

Rename to `pythia-1.4b-deduped-v0-sythetic-instruct` to be consistent

by levmckinney - opened Apr 6, 2023

Discussion

levmckinney

Apr 6, 2023

Last week EleutherAI renamed the base model to pythia-1.4b-deduped-v0 and uploaded a new pythia-1.4b-deduped. This was super annoying but to be consistent you should probably also rename this model.

levmckinney changed discussion title from Rename to be consistent with pythia model family to Rename to `pythia-1.4b-deduped-v0-sythetic-instruct` be consistent with pythia model family Apr 6, 2023

levmckinney changed discussion title from Rename to `pythia-1.4b-deduped-v0-sythetic-instruct` be consistent with pythia model family to Rename to `pythia-1.4b-deduped-v0-sythetic-instruct` be consistent Apr 6, 2023

levmckinney changed discussion title from Rename to `pythia-1.4b-deduped-v0-sythetic-instruct` be consistent to Rename to `pythia-1.4b-deduped-v0-sythetic-instruct` to be consistent Apr 6, 2023

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