Requirements
pip install -U transformers optimum auto-gptq
Transformers inference
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
dtype = torch.bfloat16 if torch.cuda.is_bf16_supported() else torch.float16
device = "auto"
model_name = "jakiAJK/granite-3.1-8b-instruct_GPTQ-int4"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, device_map= device, trust_remote_code= True, torch_dtype= dtype)
model.eval()
chat = [
{ "role": "user", "content": "List any 5 country capitals." },
]
chat = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
input_tokens = tokenizer(chat, return_tensors="pt").to('cuda')
output = model.generate(**input_tokens,
max_new_tokens=100)
output = tokenizer.batch_decode(output)
print(output)
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Model tree for jakiAJK/granite-3.1-8b-instruct_GPTQ-int4
Base model
ibm-granite/granite-3.1-8b-base
Finetuned
ibm-granite/granite-3.1-8b-instruct