maestrale-chat-v0.3-alpha-sft

<div style="width: auto; margin-left: auto; margin-right: auto"> <img src="https://i.imgur.com/3XRfTOq.jpg" alt="Mii-LLM" style="width: 100%; min-width: 400px; display: block; margin: auto;"> </div> <div style="display: flex; justify-content: space-between; width: 100%;"> <div style="display: flex; flex-direction: column; align-items: flex-end;"> <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> </div> </div> <hr style="margin-top: 1.0em; margin-bottom: 1.0em;"> <!-- header end -->

Maestrale chat alpha ༄

By @efederici and @mferraretto

Model description

• Language Model: Mistral-7b for the Italian language, continued pre-training for Italian on a curated large-scale high-quality corpus.
• Fine-Tuning: SFT performed on convs/instructions for two epochs.

v0.3

• Function calling
• Reduced default system prompt to avoid wasting tokens (pre-alignment)

This model uses ChatML prompt format:

<|im_start|>system
Sei un assistente utile.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Usage:

from transformers import (
    AutoTokenizer, 
    AutoModelForCausalLM, 
    GenerationConfig,
    TextStreamer
)
import torch

tokenizer = AutoTokenizer.from_pretrained("mii-llm/maestrale-chat-v0.3-alpha")
model = AutoModelForCausalLM.from_pretrained("mii-llm/maestrale-chat-v0.3-alpha", load_in_8bit=True, device_map="auto")

gen = GenerationConfig(
    do_sample=True,
    temperature=0.7,
    repetition_penalty=1.2,
    top_k=50,
    top_p=0.95,
    max_new_tokens=500,
    pad_token_id=tokenizer.eos_token_id,
    eos_token_id=tokenizer.convert_tokens_to_ids("<|im_end|>")
)

messages = [
    {"role": "system", "content": "Sei un assistente utile."},
    {"role": "user", "content": "{prompt}"}
]

with torch.no_grad(), torch.backends.cuda.sdp_kernel(
    enable_flash=True, 
    enable_math=False,
    enable_mem_efficient=False
):
    temp = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
    inputs = tokenizer(temp, return_tensors="pt").to("cuda")

    streamer = TextStreamer(tokenizer, skip_prompt=True)

    _ = model.generate(
        **inputs,
        streamer=streamer,
        generation_config=gen
    )

Intended uses & limitations

It's an alpha version, it's not aligned. It's a first test. We are working on alignment data and evals.

<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>