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

Libraries

How to use huggingtweets/interrogami with Transformers:

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

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

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

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use huggingtweets/interrogami with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/huggingtweets/interrogami

SGLang

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

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

interrogami

Commit History

Feb 19, 2025

20:22
Adding `safetensors` variant of this model⁠

SFconvertbot

Verified signature
8b5bc4e

Mar 23, 2022

19:41
Update model preview

boris

a1f8046
19:39
Update model preview

boris

b8a3426
19:38
Update model preview

boris

cdab295
19:33
Update model preview

boris

3e0e4e0
19:33
Update model preview

boris

1ba44c3
19:30
Update model preview

boris

21d0e1c
19:29
Update model preview

boris

59e47a9
19:25
Update model preview

boris

3aa24b2
19:19
New model from https://wandb.ai/wandb/huggingtweets/runs/2ibo4fum

boris

e938ad4
19:19
initial commit

huggingtweets-app

8d791ae

Commit History

Feb 19, 2025

Adding `safetensors` variant of this model⁠

Mar 23, 2022

Update model preview

Update model preview

Update model preview

Update model preview

Update model preview

Update model preview

Update model preview

Update model preview

New model from https://wandb.ai/wandb/huggingtweets/runs/2ibo4fum

initial commit