Instructions to use TKDKid1000/pythia-2.8b-deduped-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TKDKid1000/pythia-2.8b-deduped-GPTQ with Transformers:

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

pipe = pipeline("text-generation", model="TKDKid1000/pythia-2.8b-deduped-GPTQ")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TKDKid1000/pythia-2.8b-deduped-GPTQ")
model = AutoModelForCausalLM.from_pretrained("TKDKid1000/pythia-2.8b-deduped-GPTQ", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TKDKid1000/pythia-2.8b-deduped-GPTQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TKDKid1000/pythia-2.8b-deduped-GPTQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TKDKid1000/pythia-2.8b-deduped-GPTQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/TKDKid1000/pythia-2.8b-deduped-GPTQ

SGLang

How to use TKDKid1000/pythia-2.8b-deduped-GPTQ 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 "TKDKid1000/pythia-2.8b-deduped-GPTQ" \
    --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": "TKDKid1000/pythia-2.8b-deduped-GPTQ",
		"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 "TKDKid1000/pythia-2.8b-deduped-GPTQ" \
        --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": "TKDKid1000/pythia-2.8b-deduped-GPTQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TKDKid1000/pythia-2.8b-deduped-GPTQ with Docker Model Runner:
```
docker model run hf.co/TKDKid1000/pythia-2.8b-deduped-GPTQ
```

Model Card for TKDKid1000/pythia-2.8b-deduped-GPTQ

A quantized version of EleutherAI/pythia-2.8b-deduped using GPTQ.

Model Details

Model Description

General text generation model that is intended to be fine tuned on a downstream task for running on small devices.

Refer to the pythia-2.8b-deduped model card for more information.

Developed by: EleutherAI
Model type: GPT-NeoX
Language (NLP): English
License: MIT
Finetuned from model: EleutherAI/pythia-2.8b-deduped

Downloads last month: 10

TKDKid1000
/

pythia-2.8b-deduped-GPTQ

Model Card for TKDKid1000/pythia-2.8b-deduped-GPTQ

Model Details

Model Description

Datasets used to train TKDKid1000/pythia-2.8b-deduped-GPTQ