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| Name | Quant method | Size |
|---|---|---|
| NeuralSirKrishna-7b.Q2_K.gguf | Q2_K | 2.53GB |
| NeuralSirKrishna-7b.IQ3_XS.gguf | IQ3_XS | 2.81GB |
| NeuralSirKrishna-7b.IQ3_S.gguf | IQ3_S | 2.96GB |
| NeuralSirKrishna-7b.Q3_K_S.gguf | Q3_K_S | 2.95GB |
| NeuralSirKrishna-7b.IQ3_M.gguf | IQ3_M | 3.06GB |
| NeuralSirKrishna-7b.Q3_K.gguf | Q3_K | 3.28GB |
| NeuralSirKrishna-7b.Q3_K_M.gguf | Q3_K_M | 3.28GB |
| NeuralSirKrishna-7b.Q3_K_L.gguf | Q3_K_L | 3.56GB |
| NeuralSirKrishna-7b.IQ4_XS.gguf | IQ4_XS | 3.67GB |
| NeuralSirKrishna-7b.Q4_0.gguf | Q4_0 | 3.83GB |
| NeuralSirKrishna-7b.IQ4_NL.gguf | IQ4_NL | 3.87GB |
| NeuralSirKrishna-7b.Q4_K_S.gguf | Q4_K_S | 3.86GB |
| NeuralSirKrishna-7b.Q4_K.gguf | Q4_K | 4.07GB |
| NeuralSirKrishna-7b.Q4_K_M.gguf | Q4_K_M | 4.07GB |
| NeuralSirKrishna-7b.Q4_1.gguf | Q4_1 | 4.24GB |
| NeuralSirKrishna-7b.Q5_0.gguf | Q5_0 | 4.65GB |
| NeuralSirKrishna-7b.Q5_K_S.gguf | Q5_K_S | 4.65GB |
| NeuralSirKrishna-7b.Q5_K.gguf | Q5_K | 4.78GB |
| NeuralSirKrishna-7b.Q5_K_M.gguf | Q5_K_M | 4.78GB |
| NeuralSirKrishna-7b.Q5_1.gguf | Q5_1 | 5.07GB |
| NeuralSirKrishna-7b.Q6_K.gguf | Q6_K | 5.53GB |
| NeuralSirKrishna-7b.Q8_0.gguf | Q8_0 | 7.17GB |


1models:
2 - model: Kukedlc/NeuralKrishna-7B-v3
3 # no parameters necessary for base model
4 - model: Kukedlc/NeuralKrishna-7B-v3
5 parameters:
6 density: 0.65
7 weight: 0.36
8 - model: Kukedlc/NeuralMarioMonarch-7B-slerp
9 parameters:
10 density: 0.6
11 weight: 0.34
12 - model: liminerity/M7-7b
13 parameters:
14 density: 0.4
15 weight: 0.3
16merge_method: dare_ties
17base_model: Kukedlc/NeuralKrishna-7B-v3
18parameters:
19 int8_mask: true
20dtype: bfloat16
21random_seed: 01!pip install -qU transformers accelerate
2
3from transformers import AutoTokenizer
4import transformers
5import torch
6
7model = "Kukedlc/NeuralSirKrishna-7b"
8messages = [{"role": "user", "content": """Create an advanced theory about the origin of life on earth that is new,
9innovative, and disruptive, totally new with no resemblance to anything else but at the same time that can be real."""}]
10
11tokenizer = AutoTokenizer.from_pretrained(model)
12prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
13pipeline = transformers.pipeline(
14 "text-generation",
15 model=model,
16 torch_dtype=torch.float16,
17 device_map="auto",
18)
19
20outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
21print(outputs[0]["generated_text"])
| Metric | Value |
|---|---|
| Avg. | 76.60 |
| AI2 Reasoning Challenge (25-Shot) | 73.72 |
| HellaSwag (10-Shot) | 89.05 |
| MMLU (5-Shot) | 64.63 |
| TruthfulQA (0-shot) | 75.60 |
| Winogrande (5-shot) | 85.32 |
| GSM8k (5-shot) | 71.27 |