VertexElite v1
A LoRA fine-tuned model for tool-calling, code generation, bash/linux commands, and reasoning.
For the full merged model (no adapter needed), see: vertexelite-v1-merged
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
API Endpoints
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:de-0521a67ceb04ba4c",
"messages": [{"role": "user", "content": "list all python files"}]
}'
Python SDK
from openai import OpenAI
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:de-0521a67ceb04ba4c",
messages=[{"role": "user", "content": "find large files over 100MB"}]
)
print(response.choices[0].message.content)
Quick Start (Local)
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
# Load base + adapter
base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-0.5B-Instruct")
model = PeftModel.from_pretrained(base, "crittiksglobal/vertexelite-v1")
tokenizer = AutoTokenizer.from_pretrained("crittiksglobal/vertexelite-v1")
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]))
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
Model Details
| Property | Value |
|---|---|
| Base Model | Qwen/Qwen2.5-0.5B-Instruct |
| Type | LoRA Adapter |
| LoRA Rank | 16 |
| LoRA Alpha | 32 |
| Adapter Size | ~8 MB |
| Format | Safetensors |
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 |
|---|---|---|
| Novita.ai | API | crittiksglobal/vertexelite-v1:de-0521a67ceb04ba4c |
| PRISM CLI | CLI | prism -m vertexelite "query" |
| Ollama | Local/Cloud | liyonramesh/vertexelitev1 |
| Merged Model | Full Model | vertexelite-v1-merged |
PRISM CLI
prism -m vertexelite "your query"
Ollama
ollama run liyonramesh/vertexelitev1
Chat Format
Uses ChatML:
<|im_start|>system
{system prompt}
<|im_end|>
<|im_start|>user
{user message}
<|im_end|>
<|im_start|>assistant
{response}
<|im_end|>
Links
- Merged Version: crittiksglobal/vertexelite-v1-merged
- Ollama: liyonramesh/vertexelitev1
- Trainer Space: crittiksglobal/vertexelite-1
- PRISM API: api.liyoncorp.com
License
Apache 2.0
Creator
Created by Nirmal Liyon Founder & Full-Stack Developer at Vertex Elite Co-Founder of 6SILO
Colombo, Sri Lanka
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