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| Task | Model | Metric | Value | Change (%) |
|---|---|---|---|---|
| Winogrande | TinyLlama 1.1B Chat | Accuracy | 61.56% | - |
| Coven Tiny 1.1B | Accuracy | 61.17% | -0.63% | |
| TruthfulQA | TinyLlama 1.1B Chat | Accuracy | 30.43% | - |
| Coven Tiny 1.1B | Accuracy | 34.31% | +12.75% | |
| PIQA | TinyLlama 1.1B Chat | Accuracy | 74.10% | - |
| Coven Tiny 1.1B | Accuracy | 71.06% | -4.10% | |
| OpenBookQA | TinyLlama 1.1B Chat | Accuracy | 27.40% | - |
| Coven Tiny 1.1B | Accuracy | 30.60% | +11.68% | |
| MMLU | TinyLlama 1.1B Chat | Accuracy | 24.31% | - |
| Coven Tiny 1.1B | Accuracy | 38.03% | +56.44% | |
| Hellaswag | TinyLlama 1.1B Chat | Accuracy | 45.69% | - |
| Coven Tiny 1.1B | Accuracy | 43.44% | -4.92% | |
| GSM8K (Strict) | TinyLlama 1.1B Chat | Exact Match | 1.82% | - |
| Coven Tiny 1.1B | Exact Match | 14.71% | +708.24% | |
| GSM8K (Flexible) | TinyLlama 1.1B Chat | Exact Match | 2.65% | - |
| Coven Tiny 1.1B | Exact Match | 14.63% | +452.08% | |
| BoolQ | TinyLlama 1.1B Chat | Accuracy | 58.69% | - |
| Coven Tiny 1.1B | Accuracy | 65.20% | +11.09% | |
| ARC Easy | TinyLlama 1.1B Chat | Accuracy | 66.54% | - |
| Coven Tiny 1.1B | Accuracy | 57.24% | -13.98% | |
| ARC Challenge | TinyLlama 1.1B Chat | Accuracy | 34.13% | - |
| Coven Tiny 1.1B | Accuracy | 34.81% | +1.99% | |
| Humaneval | TinyLlama 1.1B Chat | Pass@1 | 10.98% | - |
| Coven Tiny 1.1B | Pass@1 | 10.37% | -5.56% | |
| Drop | TinyLlama 1.1B Chat | Score | 16.02% | - |
| Coven Tiny 1.1B | Score | 16.36% | +2.12% | |
| BBH | Coven Tiny 1.1B | Average | 29.02% | - |
1# Install transformers from source - only needed for versions <= v4.34
2# pip install git+https://github.com/huggingface/transformers.git
3# pip install accelerate
4
5import torch
6from transformers import pipeline
7
8pipe = pipeline("text-generation", model="raidhon/coven_tiny_1.1b_32k_orpo_alpha", torch_dtype=torch.bfloat16, device_map="auto")
9
10messages = [
11 {
12 "role": "system",
13 "content": "You are a friendly chatbot who always responds in the style of a pirate",
14 },
15 {"role": "user", "content": "How many helicopters can a human eat in one sitting?"},
16]
17prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
18outputs = pipe(prompt, max_new_tokens=2048, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
19print(outputs[0]["generated_text"])