Instructions to use huggingtweets/dkulchar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use huggingtweets/dkulchar with Transformers:

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

pipe = pipeline("text-generation", model="huggingtweets/dkulchar")

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

tokenizer = AutoTokenizer.from_pretrained("huggingtweets/dkulchar")
model = AutoModelForCausalLM.from_pretrained("huggingtweets/dkulchar", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use huggingtweets/dkulchar with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/huggingtweets/dkulchar

SGLang

How to use huggingtweets/dkulchar 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 "huggingtweets/dkulchar" \
    --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": "huggingtweets/dkulchar",
		"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 "huggingtweets/dkulchar" \
        --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": "huggingtweets/dkulchar",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use huggingtweets/dkulchar with Docker Model Runner:
```
docker model run hf.co/huggingtweets/dkulchar
```

dkulchar

Commit History

Feb 25, 2025

05:58
Adding `safetensors` variant of this model⁠

SFconvertbot

Verified signature
a8fcce7

May 22, 2021

01:49
upload flax model

patrickvonplaten

f0293bd
01:48
allow flax

patrickvonplaten

b92e690

Mar 25, 2021

18:37
New model from https://wandb.ai/wandb/huggingtweets/runs/v3hyz25i

boris

29192c6
03:16
Update model preview

boris

44ee824
03:15
Update model preview

boris

aec6d23
03:13
Update model preview

boris

5c40638
03:11
New model from https://wandb.ai/wandb/huggingtweets/runs/1gm1i2l5

boris

5bd33ee
03:11
initial commit

system HF Staff

5cbd602

Commit History

Feb 25, 2025

Adding `safetensors` variant of this model⁠

May 22, 2021

upload flax model

allow flax

Mar 25, 2021

New model from https://wandb.ai/wandb/huggingtweets/runs/v3hyz25i

Update model preview

Update model preview

Update model preview

New model from https://wandb.ai/wandb/huggingtweets/runs/1gm1i2l5

initial commit