Views
No views yet


| Task | Version | Metric | Value | Stderr | |
|---|---|---|---|---|---|
| arc_challenge | 0 | acc | 68.25 | ± | 1.36 |
| acc_norm | 70.81 | ± | 1.38 | ||
| hellaswag | 0 | acc | 70.86 | ± | 0.45 |
| acc_norm | 87.86 | ± | 0.32 | ||
| gsm8k | 0 | acc | 70.35 | ± | 1.25 |
| winogrande | 0 | acc | 84.84 | ± | 1.00 |
| mmlu | 0 | acc | 64.69 | ± | 1.00 |
| Task | Version | Metric | Value | Stderr | |
|---|---|---|---|---|---|
| truthfulqa_mc | 1 | mc1 | 46.26 | ± | 1.74 |
| mc2 | 62.42 | ± | 1.54 |
1slices:
2 - sources:
3 - model: abideen/DareVox-7B
4 layer_range: [0, 32]
5 - model: udkai/Garrulus
6 layer_range: [0, 32]
7merge_method: slerp
8base_model: abideen/DareVox-7B
9parameters:
10 t:
11 - filter: self_attn
12 value: [0, 0.5, 0.3, 0.7, 1]
13 - filter: mlp
14 value: [1, 0.5, 0.7, 0.3, 0]
15 - value: 0.5
16dtype: bfloat16
171!pip install -qU transformers accelerate
2
3from transformers import AutoTokenizer
4import transformers
5import torch
6
7model = "abideen/NexoNimbus-7B"
8messages = [{"role": "user", "content": "Explain what is Machine learning."}]
9
10tokenizer = AutoTokenizer.from_pretrained(model)
11prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
12pipeline = transformers.pipeline(
13 "text-generation",
14 model=model,
15 torch_dtype=torch.float16,
16 device_map="auto",
17)
18
19outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
20print(outputs[0]["generated_text"])