Views
No views yet
model_stockmergekit-community/L3.1-Athena-d-8Bbfloat16mergekit-community/L3.1-Athena-d-8BPedro13543/mega_blend_model - A well-balanced blend of roleplay and instruction-tuned Llama-3.1 variants.Skywork/Skywork-o1-Open-Llama-3.1-8B - Optimized for reasoning and slow-thinking capabilities.Undi95/Meta-Llama-3.1-8B-Claude - Fine-tuned on Claude Opus/Sonnet data, improving response depth and conversational engagement.mergekit-community/good_mix_model_Stock - A diverse mixture including RP-focused and knowledge-heavy datasets.1name: ZeroXClem-Llama-3.1-8B-AthenaSky-MegaMix
2base_model: mergekit-community/L3.1-Athena-d-8B
3dtype: bfloat16
4merge_method: model_stock
5models:
6 - model: Pedro13543/mega_blend_model
7 - model: Skywork/Skywork-o1-Open-Llama-3.1-8B
8 - model: Undi95/Meta-Llama-3.1-8B-Claude
9 - model: mergekit-community/good_mix_model_Stock
10tokenizer_source: mergekit-community/L3.1-Athena-d-8BSkywork-o1 integration, this model excels in logical thinking and problem-solving.Meta-Llama-3.1-8B-Claude adds better response structuring, making it more engaging in dialogue.mega_blend_model and good_mix_model_Stock, the model supports immersive roleplaying and storytelling.ollama run hf.co/ZeroXClem/Llama-3.1-8B-AthenaSky-MegaMix1from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
2import torch
3
4model_name = "ZeroXClem/Llama-3.1-8B-AthenaSky-MegaMix"
5
6# Load tokenizer & model
7tokenizer = AutoTokenizer.from_pretrained(model_name)
8model = AutoModelForCausalLM.from_pretrained(
9 model_name,
10 torch_dtype=torch.bfloat16,
11 device_map="auto"
12)
13
14# Initialize text generation pipeline
15text_generator = pipeline(
16 "text-generation",
17 model=model,
18 tokenizer=tokenizer,
19 torch_dtype=torch.bfloat16,
20 device_map="auto"
21)
22
23# Example prompt
24prompt = "Describe the significance of AI ethics in modern technology."
25
26# Generate output
27outputs = text_generator(
28 prompt,
29 max_new_tokens=200,
30 do_sample=True,
31 temperature=0.7,
32 top_k=50,
33 top_p=0.95
34)
35
36print(outputs[0]["generated_text"])
| Metric | Value |
|---|---|
| Avg. | 26.79 |
| IFEval (0-Shot) | 63.01 |
| BBH (3-Shot) | 31.39 |
| MATH Lvl 5 (4-Shot) | 27.95 |
| GPQA (0-shot) | 3.69 |
| MuSR (0-shot) | 6.90 |
| MMLU-PRO (5-shot) | 27.82 |