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Model: mii-llm/maestrale-chat-v0.3-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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- kpo
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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-v0.3-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/dgSNbTl.jpg" 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.
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- **Fine-Tuning**: SFT performed on convs/instructions for three epochs.
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- **KTO**: Aligned with KTO.
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**v0.3**
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- Function calling
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- Reduced default system prompt to avoid wasting tokens (pre-alignment)
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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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## 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-v0.3-beta")
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model = AutoModelForCausalLM.from_pretrained("mii-llm/maestrale-chat-v0.3-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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## Intended uses & limitations
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It's a beta version, but it's not `safe`.
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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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