PINDARO-HF/README.md

---
language:
- it
- en
pipeline_tag: text-generation
library_name: transformers
tags:
- llama
- italian
- general-assistant
- hf-format
- 1b
---

# PINDARO HF (General)

PINDARO HF is the Hugging Face-format release of the **general-purpose Pindaro** model.

## Model At A Glance

- Architecture: `LlamaForCausalLM`
- Model type: `llama`
- Approx. parameters: **~1.1B**
- Precision: `float16`
- Context length: `2048`
- Vocabulary size: `32002`
- Languages: Italian, English
- Primary use: general assistant text generation

## Included Files (HF)

- `model.safetensors`
- `config.json`
- `generation_config.json`
- `tokenizer.json`
- `tokenizer.model`
- `tokenizer_config.json`
- `special_tokens_map.json`
- `added_tokens.json`

This repository is **HF-only**. GGUF artifacts are intentionally not included here.

## Prompt Format

The tokenizer uses Noesis-style control tokens:

- `<|noesis|>` (id `32000`)
- `<|end|>` (id `32001`)

Configured template behavior is based on:

```jinja
{% for message in messages %}<|noesis|>
### Domanda
{{ message['content'] }}

### Risposta
{% endfor %}
```

A stable manual prompt pattern is:

```text
<|noesis|>
### Domanda
Spiega cos'e una funzione in Python.

### Risposta
```

## Quickstart (Transformers)

```python
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

model_id = "RthItalia/PINDARO-HF"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.float16,
)

prompt = "<|noesis|>
### Domanda
Spiega cos'e una funzione in Python.

### Risposta
"

inputs = tokenizer(prompt, return_tensors="pt")

# pad_token_id == eos_token_id for this model: pass attention_mask explicitly.
outputs = model.generate(
    **inputs,
    attention_mask=inputs["attention_mask"],
    max_new_tokens=120,
    do_sample=False,
)

print(tokenizer.decode(outputs[0], skip_special_tokens=False))
```

## Validation Snapshot

Last internal validation snapshot: **2026-03-02**

- HF load/config/tokenizer/model smoke tests: PASS
- Internal mini-eval (5 prompts, general quality gate): **1.00**

Notes:
- This is an internal sanity check, **not** a public benchmark suite.
- Separate GGUF quality gating is tracked outside this HF-only repo.

## Known Limitations

- Outputs can become repetitive on some long generations.
- As with other LLMs, factual and reasoning errors are possible.
- Use additional validation for high-stakes or production workflows.

## Safety

- Do not use as sole source for legal, medical, or financial decisions.
- Add moderation, logging, and domain-specific safeguards in downstream apps.

## Artifact Checksums (SHA256)

- `model.safetensors`: `778e5547c238d0e19738479562cdc310a38f5ee4c5354294a23dfccc92626e87`
- `config.json`: `ae832c409e0d6ad9c8881ec2bd287a8d7e7e9012b712513532cd3ad352ca0655`
- `generation_config.json`: `6ff47e725c0ec6d0f1895670de7ee68e61a4f99703f6c8e89aea6ab14ea02dc3`
- `tokenizer.json`: `51433f06369ac3e597dfa23a811215e3511b8f86588a830ded72344b76a193ee`
- `tokenizer.model`: `9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347`
- `tokenizer_config.json`: `02ca6d3ddfa1112eec7bd5f22a0e682338b5b2da8ddb6761e9d25e6d7b8188d0`
- `special_tokens_map.json`: `d7805e093432afcde852968cdeba3de08a6fe66e77609f4701decb87fc492f33`
- `added_tokens.json`: `ece349d292e246eac9a9072c1730f023e61567984a828fb0d25dccb14e3b7592`