README.md

metadata

license: llama3
tags:
  - moe
  - merge
  - llama-3
language:
  - en
  - tr
pipeline_tag: text-generation
library_name: transformers

💻 For English

Megatron_llama3_2x8B is a Mixure of Experts (MoE) (two llama3 models)

!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "Eurdem/Megatron_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 who always responds friendly."},
    {"role": "user", "content": "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,
                          eos_token_id = tokenizer.eos_token_id
                      )
response = outputs[0][input_ids.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True))

Megatron_llama3_2x8B

💻 Türkçe İçin

!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "Eurdem/Megatron_llama3_2x8B"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, device_map="auto", load_in_4bit= True)

messages = [
    {"role": "system", "content": "Sen Defne isimli Türkçe konuşan bir chatbotsun."},
    {"role": "user", "content": "Sana 2 sorum var. 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,
                          eos_token_id = tokenizer.eos_token_id
                      )
response = outputs[0][input_ids.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True))

Çıktı

Sorunuzun 2. kısmı için, f(x) = 3x^2 + 4x + 12 formülünü ele alalım. f(3)'ün hesabını yapalım:

f(3) = 3(3)^2 + 4(3) + 12
= 3(9) + 12 + 12
= 27 + 24
= 51

Bu nedenle, f(3) 51'dir.```