Instructions to use crittiksglobal/vertexelite-v1-merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use crittiksglobal/vertexelite-v1-merged with Transformers:

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

pipe = pipeline("text-generation", model="crittiksglobal/vertexelite-v1-merged")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("crittiksglobal/vertexelite-v1-merged")
model = AutoModelForCausalLM.from_pretrained("crittiksglobal/vertexelite-v1-merged", 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 crittiksglobal/vertexelite-v1-merged with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/crittiksglobal/vertexelite-v1-merged

SGLang

How to use crittiksglobal/vertexelite-v1-merged 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 "crittiksglobal/vertexelite-v1-merged" \
    --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": "crittiksglobal/vertexelite-v1-merged",
		"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 "crittiksglobal/vertexelite-v1-merged" \
        --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": "crittiksglobal/vertexelite-v1-merged",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use crittiksglobal/vertexelite-v1-merged with Docker Model Runner:
```
docker model run hf.co/crittiksglobal/vertexelite-v1-merged
```

VertexElite v1 (Merged)

A fully merged model specialized for tool-calling, function execution, code generation, bash commands, and reasoning.

This is the merged version - no adapter needed! Ready to run directly.

API Endpoints

HuggingFace Inference Endpoint (Public - No Auth!)

curl https://bqkeuwh1lbn748co.us-east-1.aws.endpoints.huggingface.cloud/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "crittiksglobal/vertexelite-v1-merged",
    "messages": [{"role": "user", "content": "list all python files"}]
  }'

Novita.ai (OpenAI Compatible)

curl https://api.novita.ai/dedicated/v1/openai/chat/completions \
  -H "Authorization: Bearer YOUR_NOVITA_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "crittiksglobal/vertexelite-v1-merged:de-628e9b518ccd873f",
    "messages": [{"role": "user", "content": "find large files over 100MB"}]
  }'

Python SDK

from openai import OpenAI

# Using HuggingFace Endpoint (Public)
client = OpenAI(
    base_url="https://bqkeuwh1lbn748co.us-east-1.aws.endpoints.huggingface.cloud/v1",
    api_key="none"  # Public endpoint
)

# Or using Novita.ai
client = OpenAI(
    base_url="https://api.novita.ai/dedicated/v1/openai",
    api_key="YOUR_NOVITA_KEY"
)

response = client.chat.completions.create(
    model="crittiksglobal/vertexelite-v1-merged",
    messages=[{"role": "user", "content": "find large files over 100MB"}]
)
print(response.choices[0].message.content)

Quick Start (Local)

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("crittiksglobal/vertexelite-v1-merged")
tokenizer = AutoTokenizer.from_pretrained("crittiksglobal/vertexelite-v1-merged")

prompt = "<|im_start|>user\nList all files in current directory<|im_end|>\n<|im_start|>assistant\n"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0]))

Model Details

Property	Value
Base Model	Qwen/Qwen2.5-0.5B-Instruct
Type	Merged (Full Model)
Parameters	494M
Size	~1 GB
Format	Safetensors

Capabilities

Tool/Function Calling - Execute functions from natural language
Bash/Linux Commands - Generate correct shell commands
Code Generation - Write and understand code
Reasoning & Problem Solving - Logical analysis
Defect Detection - Find bugs and issues
Instruction Following - Follow complex instructions

Training Data

Dataset	Samples	Purpose
NousResearch/hermes-function-calling-v1	1,000	Tool calling
teknium/OpenHermes-2.5	5,000	General + code
aelhalili/bash-commands-dataset	840	Bash commands
harpomaxx/unix-commands	2,540	Unix/Linux commands
moremilk/Reasoning_Problem_Solving_Dataset	2,000	Reasoning
mcanoglu/defect-detection	2,000	Bug detection
nickrosh/Evol-Instruct-Code-80k-v1	2,000	Code generation

Total: 15,380+ training examples

Usage Examples

Bash Commands

User: "find all python files modified today"
Assistant: find . -name "*.py" -mtime 0

Tool Calling

User: "What's the weather in Tokyo?"
Assistant: <functioncall>{"name": "get_weather", "arguments": {"city": "Tokyo"}}</functioncall>

Code Generation

User: "Write a function to check if a number is prime"
Assistant: def is_prime(n):
    if n < 2:
        return False
    for i in range(2, int(n**0.5) + 1):
        if n % i == 0:
            return False
    return True

All Inference Options

Provider	Type	Endpoint/Model
HuggingFace	Public API	`bqkeuwh1lbn748co.us-east-1.aws.endpoints.huggingface.cloud`
Novita.ai	API	`crittiksglobal/vertexelite-v1-merged:de-628e9b518ccd873f`
Ollama	Local/Cloud	`liyonramesh/vertexelitev1`
PRISM CLI	CLI	`prism -m vertexelite "query"`
vLLM	Self-hosted	See below

Ollama

ollama run liyonramesh/vertexelitev1

vLLM

python -m vllm.entrypoints.openai.api_server \
  --model crittiksglobal/vertexelite-v1-merged \
  --port 8000

PRISM CLI

prism -m vertexelite "your query"

Chat Format

Uses ChatML:

<|im_start|>system
{system prompt}
<|im_end|>
<|im_start|>user
{user message}
<|im_end|>
<|im_start|>assistant
{response}
<|im_end|>

License

Apache 2.0

Creator

Created by Nirmal Liyon Founder & Full-Stack Developer at Vertex Elite Co-Founder of 6SILO

Colombo, Sri Lanka

Downloads last month: 14

Safetensors

Model size

0.5B params

Tensor type

BF16

Model tree for crittiksglobal/vertexelite-v1-merged

Base model

Qwen/Qwen2.5-0.5B

Finetuned

Qwen/Qwen2.5-0.5B-Instruct

Finetuned

(925)

this model

crittiksglobal
/

vertexelite-v1-merged

VertexElite v1 (Merged)

API Endpoints

HuggingFace Inference Endpoint (Public - No Auth!)

Novita.ai (OpenAI Compatible)

Python SDK

Quick Start (Local)

Model Details

Capabilities

Training Data

Usage Examples

Bash Commands

Tool Calling

Code Generation

All Inference Options

Ollama

vLLM

PRISM CLI

Chat Format

Links

License

Creator

Model tree for crittiksglobal/vertexelite-v1-merged

Datasets used to train crittiksglobal/vertexelite-v1-merged

Space using crittiksglobal/vertexelite-v1-merged 1