Instructions to use iamshnoo/combined_no_africa_with_metadata_1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use iamshnoo/combined_no_africa_with_metadata_1b with Transformers:

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

pipe = pipeline("text-generation", model="iamshnoo/combined_no_africa_with_metadata_1b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("iamshnoo/combined_no_africa_with_metadata_1b")
model = AutoModelForCausalLM.from_pretrained("iamshnoo/combined_no_africa_with_metadata_1b", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use iamshnoo/combined_no_africa_with_metadata_1b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "iamshnoo/combined_no_africa_with_metadata_1b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "iamshnoo/combined_no_africa_with_metadata_1b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/iamshnoo/combined_no_africa_with_metadata_1b

SGLang

How to use iamshnoo/combined_no_africa_with_metadata_1b 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 "iamshnoo/combined_no_africa_with_metadata_1b" \
    --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": "iamshnoo/combined_no_africa_with_metadata_1b",
		"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 "iamshnoo/combined_no_africa_with_metadata_1b" \
        --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": "iamshnoo/combined_no_africa_with_metadata_1b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use iamshnoo/combined_no_africa_with_metadata_1b with Docker Model Runner:
```
docker model run hf.co/iamshnoo/combined_no_africa_with_metadata_1b
```

iamshnoo commited on Apr 2

Commit

c1acc84

verified ·

1 Parent(s): f655af2

Update model card from W&B metadata

Browse files

Files changed (1) hide show

README.md +1 -1

README.md CHANGED Viewed

@@ -55,4 +55,4 @@ This model is part of the metadata localization release. Related checkpoints and
 - Training data source: [News on the Web (NOW) Corpus](https://www.english-corpora.org/now/)
 - Project repository: [https://github.com/iamshnoo/metadata_localization](https://github.com/iamshnoo/metadata_localization)
-Last synced: `2026-04-01 21:51:54 UTC`

 - Training data source: [News on the Web (NOW) Corpus](https://www.english-corpora.org/now/)
 - Project repository: [https://github.com/iamshnoo/metadata_localization](https://github.com/iamshnoo/metadata_localization)
+Last synced: `2026-04-02 01:19:56 UTC`