Instructions to use BreadAi/gpt-Youtube with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use BreadAi/gpt-Youtube with Transformers:

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

pipe = pipeline("text-generation", model="BreadAi/gpt-Youtube")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("BreadAi/gpt-Youtube")
model = AutoModelForCausalLM.from_pretrained("BreadAi/gpt-Youtube")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use BreadAi/gpt-Youtube with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/BreadAi/gpt-Youtube

SGLang

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

Docker Model Runner
How to use BreadAi/gpt-Youtube with Docker Model Runner:
```
docker model run hf.co/BreadAi/gpt-Youtube
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

this is trained on 180K YouTube comments.

this is trained for 100k steps.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	24.86
ARC (25-shot)	23.29
HellaSwag (10-shot)	26.34
MMLU (5-shot)	23.54
TruthfulQA (0-shot)	48.63
Winogrande (5-shot)	48.93
GSM8K (5-shot)	0.0
DROP (3-shot)	3.32

Downloads last month: 1,338

Safetensors

Model size

0.2B params

Tensor type

F32

Model tree for BreadAi/gpt-Youtube

Quantizations

2 models

BreadAi
/

gpt-Youtube

Open LLM Leaderboard Evaluation Results

Model tree for BreadAi/gpt-Youtube

Dataset used to train BreadAi/gpt-Youtube

Spaces using BreadAi/gpt-Youtube 35