---
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
tags:
  - text-generation
  - gpt2
  - pytorch
  - enterprise-automation
---

# Vytre Core

Vytre Core is a compact, domain-specific text-generation model trained on
synthetic enterprise-workforce tasks: department creation, agent definition,
workflow planning, task decomposition, governance checks, and tool routing.

## Model files

This repository is self-contained. It contains a standard Transformers GPT-2
checkpoint and tokenizer, not a LoRA adapter. Do **not** combine it with the
legacy `vytre-core-upload` LoRA template or an external Llama base model.

## Load with Transformers

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "tarvico/vytre-core"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

prompt = (
    "You are Vytre, an enterprise workforce operating intelligence model.\\n"
    "Input: Create marketing department\\n"
    "Output: "
)
inputs = tokenizer(prompt, return_tensors="pt")
tokens = model.generate(
    **inputs,
    max_new_tokens=80,
    do_sample=False,
    pad_token_id=tokenizer.pad_token_id,
    eos_token_id=tokenizer.eos_token_id,
)
print(tokenizer.decode(tokens[0], skip_special_tokens=True))
```

## Limitations

This is a small specialised model, not a general-purpose chat model. Use the
prompt format above and keep requests close to the listed operational domains.
Validate generated JSON before taking actions from it.