Instructions to use Ba2han/Tinypus-1.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Ba2han/Tinypus-1.5B with Transformers:

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

pipe = pipeline("text-generation", model="Ba2han/Tinypus-1.5B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Ba2han/Tinypus-1.5B")
model = AutoModelForCausalLM.from_pretrained("Ba2han/Tinypus-1.5B", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Ba2han/Tinypus-1.5B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Ba2han/Tinypus-1.5B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Ba2han/Tinypus-1.5B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Ba2han/Tinypus-1.5B

SGLang

How to use Ba2han/Tinypus-1.5B 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 "Ba2han/Tinypus-1.5B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Ba2han/Tinypus-1.5B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "Ba2han/Tinypus-1.5B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Ba2han/Tinypus-1.5B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Ba2han/Tinypus-1.5B with Docker Model Runner:
```
docker model run hf.co/Ba2han/Tinypus-1.5B
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

*drumroll please*

Introducing Tinypus!

I passthrough merged base Tiny Llama Chat with itself, then fine-tuned with around 1/3 of Platypus dataset.

Observations:

It's smarter (I think?)
It sometimes throws "### Instruction:" line. This could be due to the platypus dataset, or the fact that I know jackshit about programming. You can add it to "custom stopping strings" in oobaboga.
It may be possible to train very specialized mini experts and merge them???

Template

Same with TinyLlama/TinyLlama-1.1B-Chat-v1.0

Merge details

slices:

sources:
- model: E://text-generation-webui//models//TinyLlama
  
  layer_range: [0, 12]
sources:
- model: E://text-generation-webui//models//TinyLlama
  
  layer_range: [4, 22]

merge_method: passthrough

dtype: bfloat16

QLoRA Details

Chunk Length: 1152 R/A: 64/128 Epoch: 1 q-k-v-o

Downloads last month: 73

Safetensors

Model size

1B params

Tensor type

BF16

Model tree for Ba2han/Tinypus-1.5B

Quantizations

1 model

Ba2han
/

Tinypus-1.5B

Model tree for Ba2han/Tinypus-1.5B

Dataset used to train Ba2han/Tinypus-1.5B