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

Libraries

How to use ppopiolek/tinyllama_merged_test with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ppopiolek/tinyllama_merged_test")
model = AutoModelForCausalLM.from_pretrained("ppopiolek/tinyllama_merged_test", 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 ppopiolek/tinyllama_merged_test with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/ppopiolek/tinyllama_merged_test

SGLang

How to use ppopiolek/tinyllama_merged_test 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 "ppopiolek/tinyllama_merged_test" \
    --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": "ppopiolek/tinyllama_merged_test",
		"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 "ppopiolek/tinyllama_merged_test" \
        --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": "ppopiolek/tinyllama_merged_test",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Desktop
Docker Model Runner
How to use ppopiolek/tinyllama_merged_test with Docker Model Runner:
```
docker model run hf.co/ppopiolek/tinyllama_merged_test
```

tinyllama_merged_test / README.md

ppopiolek

Adding Evaluation Results (#1)

d40ddfc verified over 2 years ago

preview code

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	---
	language:
	- en
	license: apache-2.0
	tags:
	- text-generation-inference
	- transformers
	- unsloth
	- llama
	- trl
	base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
	widget:
	- example_title: Fibonacci (Python)
	messages:
	- role: system
	content: You are an all-knowing chatbot!
	- role: user
	content: Write me a function to calculate the first 10 digits of the fibonacci
	sequence in Python and print it out to the CLI.
	model-index:
	- name: tinyllama_merged_test
	results:
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: AI2 Reasoning Challenge (25-Shot)
	type: ai2_arc
	config: ARC-Challenge
	split: test
	args:
	num_few_shot: 25
	metrics:
	- type: acc_norm
	value: 37.2
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ppopiolek/tinyllama_merged_test
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: HellaSwag (10-Shot)
	type: hellaswag
	split: validation
	args:
	num_few_shot: 10
	metrics:
	- type: acc_norm
	value: 61.32
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ppopiolek/tinyllama_merged_test
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: MMLU (5-Shot)
	type: cais/mmlu
	config: all
	split: test
	args:
	num_few_shot: 5
	metrics:
	- type: acc
	value: 25.7
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ppopiolek/tinyllama_merged_test
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: TruthfulQA (0-shot)
	type: truthful_qa
	config: multiple_choice
	split: validation
	args:
	num_few_shot: 0
	metrics:
	- type: mc2
	value: 38.72
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ppopiolek/tinyllama_merged_test
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: Winogrande (5-shot)
	type: winogrande
	config: winogrande_xl
	split: validation
	args:
	num_few_shot: 5
	metrics:
	- type: acc
	value: 61.25
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ppopiolek/tinyllama_merged_test
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: GSM8k (5-shot)
	type: gsm8k
	config: main
	split: test
	args:
	num_few_shot: 5
	metrics:
	- type: acc
	value: 1.9
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ppopiolek/tinyllama_merged_test
	name: Open LLM Leaderboard
	---

	# Uploaded model

	- Developed by: ppopiolek
	- License: apache-2.0
	- Finetuned from model : TinyLlama/TinyLlama-1.1B-Chat-v1.0

	This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.

	[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

	# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
	Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_ppopiolek__tinyllama_merged_test)

	\| Metric \|Value\|
	\|---------------------------------\|----:\|
	\|Avg. \|37.68\|
	\|AI2 Reasoning Challenge (25-Shot)\|37.20\|
	\|HellaSwag (10-Shot) \|61.32\|
	\|MMLU (5-Shot) \|25.70\|
	\|TruthfulQA (0-shot) \|38.72\|
	\|Winogrande (5-shot) \|61.25\|
	\|GSM8k (5-shot) \| 1.90\|