初始化项目，由ModelHub XC社区提供模型
Model: mii-llm/maestrale-chat-v0.4-beta Source: Original Platform
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README.md
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README.md
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---
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language:
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- it
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license: cc-by-nc-4.0
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tags:
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- sft
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- it
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- mistral
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- chatml
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- axolotl
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prompt_template: <|im_start|>system {system_message}<|im_end|> <|im_start|>user {prompt}<|im_end|>
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<|im_start|>assistant
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model-index:
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- name: maestrale-chat-v0.4-beta
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results: []
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---
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<div style="width: auto; margin-left: auto; margin-right: auto">
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<img src="https://i.imgur.com/yu0sVwC.png" alt="Mii-LLM" style="width: 100%; min-width: 400px; display: block; margin: auto;">
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</div>
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<div style="display: flex; justify-content: space-between; width: 100%;">
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<div style="display: flex; flex-direction: column; align-items: flex-end;">
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<p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://buy.stripe.com/8wM00Sf3vb3H3pmfYY">Want to contribute? Please donate! This will let us work on better datasets and models!</a></p>
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</div>
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</div>
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<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
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<!-- header end -->
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# Maestrale chat beta ༄
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By @efederici and @mferraretto
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## Model description
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- **Language Model**: Mistral-7b for the Italian language, continued pre-training for Italian on a curated large-scale high-quality corpus, merged with [occiglot](https://huggingface.co/occiglot/occiglot-7b-eu5).
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- **Fine-Tuning**: SFT performed on 1.7M convs/instructions for 2 epochs.
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- **DPO**: Aligned with DPO on multiple datasets.
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**v0.4**
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- Agent
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- Improved truthfullness
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- Improved Math & Reasoning capabilities
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- Mermaid mindmaps
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- More latin translations, poems, ...
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This model uses ChatML prompt format:
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```
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<|im_start|>system
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Sei un assistente utile.<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant
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```
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## Scores
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| Tasks |Version|Filter|n-shot| Metric |Value | |Stderr|
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|------------|------:|------|-----:|--------|-----:|---|-----:|
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|hellaswag_it| 1|none | 0|acc |0.5270|± |0.0052|
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| | |none | 0|acc_norm|0.7037|± |0.0048|
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|arc_it | 1|none | 0|acc |0.1771|± |0.0112|
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| | |none | 0|acc_norm|0.5218|± |0.0146|
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|m_mmlu_it | 0|none | 5|acc |0.5623|± |0.0043|
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## Usage:
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```python
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from transformers import (
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AutoTokenizer,
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AutoModelForCausalLM,
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GenerationConfig,
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TextStreamer
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)
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import torch
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tokenizer = AutoTokenizer.from_pretrained("mii-llm/maestrale-chat-v0.4-beta")
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model = AutoModelForCausalLM.from_pretrained("mii-llm/maestrale-chat-v0.4-beta", load_in_8bit=True, device_map="auto")
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gen = GenerationConfig(
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do_sample=True,
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temperature=0.7,
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repetition_penalty=1.2,
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top_k=50,
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top_p=0.95,
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max_new_tokens=500,
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pad_token_id=tokenizer.eos_token_id,
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eos_token_id=tokenizer.convert_tokens_to_ids("<|im_end|>")
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)
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streamer = TextStreamer(tokenizer, skip_prompt=True)
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messages = [
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{"role": "system", "content": "Sei un assistente utile."},
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{"role": "user", "content": "{prompt}"}
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]
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with torch.no_grad():
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temp = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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inputs = tokenizer(temp, return_tensors="pt").to("cuda")
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_ = model.generate(
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**inputs,
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streamer=streamer,
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generation_config=gen
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)
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```
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## Examples
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### Mindmaps
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```python
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messages = [
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{"role": "system", "content": "Fornisci una mindmap Mermaid sull'argomento in input."},
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{"role": "user", "content": "Argomento: [argomento]"}
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]
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```
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### SQL
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```python
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schema = "[db schema]"
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messages = [
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{"role": "system", "content": f"Sei un assistente SQL e il tuo compito è convertire la domanda dell'utente in codice SQL valido rispetto allo schema del database fornito.\n\nSchema:\n```sql\n{schema}\n```"},
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{"role": "user", "content": "Conta il numero di X prodotti dall'azienda Y"}
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]
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```
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### Article from index
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```python
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messages = [
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{"role": "system", "content": "Sei un assistente utile."},
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{"role": "user", "content": (
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"Scrivi un articolo a partire dal titolo e dall'indice dei contenuti.\n\n"
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"Titolo: [titolo]\n\n"
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"Indice:\n\n"
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"1. Introduzione\n"
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"2. [heading]\n"
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"..."
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)}
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]
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```
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## Intended uses & limitations
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It's a beta version; it's quite `safe`, and it can refuse to answer to toxic questions.
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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