Instructions to use EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat with Transformers:

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

pipe = pipeline("text-generation", model="EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat")
model = AutoModelForCausalLM.from_pretrained("EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat

SGLang

How to use EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat 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 "EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat" \
    --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": "EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat",
		"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 "EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat" \
        --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": "EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat with Docker Model Runner:
```
docker model run hf.co/EleutherAI/deep-ignorance-e2e-strong-filter-cb-lat
```

Improve model card: Add pipeline tag, library name, and paper/project/code links

by nielsr HF Staff - opened Aug 13, 2025

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+30

-27

nielsr

Aug 13, 2025

This PR enhances the model card for the Deep Ignorance model suite by:

Adding the pipeline_tag: text-generation to the metadata, which improves discoverability on the Hugging Face Hub (e.g., via https://huggingface.co/models?pipeline_tag=text-generation).
Specifying library_name: transformers in the metadata, indicating its compatibility with the Hugging Face Transformers library and enabling the "Use in Transformers" widget on the model page.
Adding explicit links to the official paper (on Hugging Face Papers), the project's dedicated webpage, and the GitHub repository. These were either missing or incorrectly linked in the original content, and their addition provides a more comprehensive and accessible overview for users.

Please review and merge this PR.

Improve model card: Add pipeline tag, library name, and paper/project/code linksbe69d6b6

Kyle1668 changed pull request status to merged Aug 13, 2025

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment