Instructions to use dominguesm/tiny-random-canarim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use dominguesm/tiny-random-canarim with Transformers:

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

pipe = pipeline("text-generation", model="dominguesm/tiny-random-canarim")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("dominguesm/tiny-random-canarim")
model = AutoModelForCausalLM.from_pretrained("dominguesm/tiny-random-canarim")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use dominguesm/tiny-random-canarim with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/dominguesm/tiny-random-canarim

SGLang

How to use dominguesm/tiny-random-canarim 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 "dominguesm/tiny-random-canarim" \
    --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": "dominguesm/tiny-random-canarim",
		"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 "dominguesm/tiny-random-canarim" \
        --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": "dominguesm/tiny-random-canarim",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use dominguesm/tiny-random-canarim with Docker Model Runner:
```
docker model run hf.co/dominguesm/tiny-random-canarim
```

tiny-random-canarim

This is a tiny random Llama model derived from "dominguesm/canarim-7b".

See make_tiny_model.py for how this was done.

This is useful for functional testing (not quality generation, since its weights are random and the tokenizer has been shrunk to 3k items)

Thanks to Stas Bekman for the code.

Downloads last month: 19

Safetensors

Model size

168k params

Tensor type

BF16

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tiny-random-canarim

tiny-random-canarim

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