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, merged with occiglot.
- Fine-Tuning: SFT performed on 1.7M convs/instructions for 2 epochs.
v0.4
- Agent
- Improved truthfullness
- Improved Math & Reasoning capabilities
- Mermaid mindmaps
- More latin translations, poems, ...
This model uses ChatML prompt format:
<|im_start|>system
Sei un assistente utile.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Scores
Tasks | Version | Filter | n-shot | Metric | Value | Stderr | |
---|---|---|---|---|---|---|---|
hellaswag_it | 1 | none | 0 | acc | 0.5220 | ± | 0.0052 |
none | 0 | acc_norm | 0.6887 | ± | 0.0048 | ||
arc_it | 1 | none | 0 | acc | 0.1762 | ± | 0.0111 |
none | 0 | acc_norm | 0.5090 | ± | 0.0146 | ||
m_mmlu_it | 0 | none | 5 | acc | 0.569 | ± | 0.0043 |
Usage:
from transformers import (
AutoTokenizer,
AutoModelForCausalLM,
GenerationConfig,
TextStreamer
)
import torch
tokenizer = AutoTokenizer.from_pretrained("mii-llm/maestrale-chat-v0.4-alpha-sft")
model = AutoModelForCausalLM.from_pretrained("mii-llm/maestrale-chat-v0.4-alpha-sft", 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|>")
)
streamer = TextStreamer(tokenizer, skip_prompt=True)
messages = [
{"role": "system", "content": "Sei un assistente utile."},
{"role": "user", "content": "{prompt}"}
]
with torch.no_grad():
temp = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(temp, return_tensors="pt").to("cuda")
_ = model.generate(
**inputs,
streamer=streamer,
generation_config=gen
)
Intended uses & limitations
It's an alpha version; it's not safe
, but it can refuse to answer.
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