Instructions to use pjool/business-news-generator_moredecay with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use pjool/business-news-generator_moredecay with Transformers:

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

pipe = pipeline("text-generation", model="pjool/business-news-generator_moredecay")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("pjool/business-news-generator_moredecay")
model = AutoModelForCausalLM.from_pretrained("pjool/business-news-generator_moredecay", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use pjool/business-news-generator_moredecay with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/pjool/business-news-generator_moredecay

SGLang

How to use pjool/business-news-generator_moredecay 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 "pjool/business-news-generator_moredecay" \
    --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": "pjool/business-news-generator_moredecay",
		"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 "pjool/business-news-generator_moredecay" \
        --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": "pjool/business-news-generator_moredecay",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use pjool/business-news-generator_moredecay with Docker Model Runner:
```
docker model run hf.co/pjool/business-news-generator_moredecay
```

business-news-generator_moredecay

This model is a fine-tuned version of HuggingFaceTB/SmolLM2-135M on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 2.8505

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0005
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
3.3356	0.1333	200	3.4433
3.0754	0.2667	400	3.3116
2.996	0.4	600	3.2476
2.8609	0.5333	800	3.1403
2.8215	0.6667	1000	3.0865
2.6704	0.8	1200	3.0253
2.6402	0.9333	1400	2.9448
2.0893	1.0667	1600	3.0050
1.6794	1.2	1800	2.9873
1.6491	1.3333	2000	2.9438
1.5772	1.4667	2200	2.8991
1.5501	1.6	2400	2.8744
1.4884	1.7333	2600	2.8597
1.4942	1.8667	2800	2.8518
1.5178	2.0	3000	2.8505

Framework versions

Transformers 4.56.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.0

Downloads last month: 9

Safetensors

Model size

0.1B params

Tensor type

F32

Model tree for pjool/business-news-generator_moredecay

Base model

HuggingFaceTB/SmolLM2-135M

Finetuned

(932)

this model