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1base_model: meta-llama/Meta-Llama-3-8B
2gate_mode: hidden
3experts:
4 - source_model: abacusai/Llama-3-Smaug-8B
5 positive_prompts:
6 - "chat"
7 - "assistant"
8 - "tell me"
9 - "explain"
10 - "I want"
11 - source_model: cognitivecomputations/dolphin-2.9-llama3-8b
12 positive_prompts:
13 - "math"
14 - "mathematics"
15 - "code"
16 - "engineering"
17 - "solve"
18 - "logic"
19 - "rationality"
20 - "puzzle"
21 - "solve"
22 - source_model: Weyaxi/Einstein-v6.1-Llama3-8B
23 positive_prompts:
24 - "science"
25 - "medical"
26 - "physics"
27 - "engineering"
28 - "math"
29 - "logic"
30 - "rationality"
31 - "mathematics"
32 - "solve"
33 - source_model: dreamgen-preview/opus-v1.2-llama-3-8b-base-run3.4-epoch2
34 positive_prompts:
35 - "story"
36 - "roleplay"
37 - "role-play"
38 - "storywriting"
39 - "character"
40 - "narrative"
41 - "creative"| Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
|---|---|---|---|---|---|---|
| 66.39 | 61.26 | 82.38 | 66.67 | 50.15 | 77.66 | 60.2 |
1!pip install -qU transformers accelerate
2
3from transformers import AutoTokenizer
4import transformers
5import torch
6
7model = "saucam/Skyro-4X8B"
8messages = [{"role": "user", "content": "In a student council election, candidate A got 20% of the votes while candidate B got 50% more than candidate A's votes. The rest of the votes was given to candidate C. If there were 100 voters, how many votes did candidate C get?"}]
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"])config.json: 100%|██████████████████████████████████████████████████████████████| 878/878 [00:00<00:00, 4.18MB/s]
model.safetensors.index.json: 100%|██████████████████████████████████████████| 53.5k/53.5k [00:00<00:00, 101MB/s]
model-00001-of-00006.safetensors: 100%|█████████████████████████████████████| 9.89G/9.89G [03:47<00:00, 43.4MB/s]
model-00002-of-00006.safetensors: 100%|█████████████████████████████████████| 9.98G/9.98G [03:23<00:00, 49.0MB/s]
model-00003-of-00006.safetensors: 100%|█████████████████████████████████████| 9.98G/9.98G [03:44<00:00, 44.5MB/s]
model-00004-of-00006.safetensors: 100%|█████████████████████████████████████| 9.90G/9.90G [03:30<00:00, 46.9MB/s]
model-00005-of-00006.safetensors: 100%|█████████████████████████████████████| 9.08G/9.08G [03:08<00:00, 48.1MB/s]
model-00006-of-00006.safetensors: 100%|█████████████████████████████████████| 1.05G/1.05G [00:20<00:00, 51.3MB/s]
Downloading shards: 100%|█████████████████████████████████████████████████████████| 6/6 [17:58<00:00, 179.78s/it]
Loading checkpoint shards: 100%|███████████████████████████████████████████████████| 6/6 [01:27<00:00, 14.59s/it]
WARNING:root:Some parameters are on the meta device device because they were offloaded to the cpu.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
<|im_start|>user
In a student council election, candidate A got 20% of the votes while candidate B got 50% more than candidate A's votes. The rest of the votes was given to candidate C. If there were 100 voters, how many votes did candidate C get?<|im_end|>
<|im_start|>assistant
Let's denote the number of votes candidate A got as \( A \).
Candidate B got 50% more votes than candidate A, so candidate B got \( A + 0.5A = 1.5A \) votes.
Candidate C got the rest of the votes, which means \( C = 100 - (A + 1.5A) \).
We know that candidate A got 20% of the votes, so \( A = 20\% \times 100 = 20 \).
Now we can calculate candidate C's votes:
\( C = 100 - (20 + 1.5 \times 20) \)
\( C = 100 - (20 + 30) \)
\( C = 100 - 50 \)
\( C = 50 \).
Therefore, candidate C got 50 votes.<|im_end|>