初始化项目，由ModelHub XC社区提供模型

Model: RthItalia/PINDARO-HF
Source: Original Platform

README.md

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+---
+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`