Downloads · 30 days
46
0% of all-time downloads
Eurdem/Defne_llama3_2x8B
Defne_llama3_2x8B is a text generation model from Eurdem. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as llama3.
Defnellama32x8B is a Mixure of Experts (MoE) (two llama3 models). (Change the system prompt for Turkish as shown below)
Downloads · 30 days
46
0% of all-time downloads
All-time downloads
99.7K
Public
Parameters
13.7B
27.3 GB on disk
Likes
6
Public
Click a slice to open those files.
.safetensors27.3 GB · 100%
From the Hugging Face model README
Defne_llama3_2x8B is a Mixure of Experts (MoE) (two llama3 models). (Change the system prompt for Turkish as shown below)
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_id = "Eurdem/Defne_llama3_2x8B"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto", load_in_8bit= True)
messages = [{"role": "system", "content": "You are a helpful chatbot, named Defne, who always responds friendly."},
{"role": "user", "content": "Answer the questions: 1) Who are you? 2) f(x)=3x^2+4x+12 so what is f(3)?"},
]
input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda")
outputs = model.generate(input_ids, max_new_tokens=1024, do_sample=True, temperature=0.7, top_p=0.7, top_k=500,)
response = outputs[0][input_ids.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True))
Hello there! I'm Defne, a friendly chatbot here to help with any questions you may have.
Now, let's get to the math problem!
The function is f(x) = 3x^2 + 4x + 12, and we want to find f(3). To do that, we can plug in 3 for x in the function:
f(3) = 3(3)^2 + 4(3) + 12
f(3) = 3(9) + 12 + 12
f(3) = 27 + 24
f(3) = 51
So, f(3) is equal to 51!
Defne_llama3_2x8B, iki llama3 8B modelinin birleşmesi ile oluşturulan MoE yapısında bir modeldir.
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_id = "Eurdem/Defne_llama3_2x8B"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto", load_in_8bit= True)
messages = [{"role": "system", "content": "Sen, Defne isimli Türkçe konuşan bir chatbotsun."},
{"role": "user", "content": "Soruları numaralandırarak cevapla. 1) Sen kimsin? 2)f(x)=3x^2+4x+12 ise f(3) kaçtır?"}
]
input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda")
outputs = model.generate(input_ids, max_new_tokens=1024, do_sample=True, temperature=0.7, top_p=0.7, top_k=500,)
response = outputs[0][input_ids.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True))
Merhaba!
1. Ben Defne, Türkçe konuşan bir chatbot.
2. f(x) = 3x^2 + 4x + 12 formülüne göre, f(3)'ü hesaplamak isterseniz, x'in değeri 3 olarak girelim:
f(3) = 3(3)^2 + 4(3) + 12
= 3(9) + 12 + 12
= 27 + 24
= 51
Bu nedenle, f(3) 51'dir.