GPTQ Quants
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Model Name: Phi-nut-Butter-Codebagel-v1 Quantization Data: 4bit GPTQ
This is a GPTQ 4 bit quantization of thesven/Phi-nut-Butter-Codebagel-v1. For more details on the model please see the model card.
This model is designed to improve instruction-following capabilities, particularly for code-related tasks.
<|system|>
{system_message} <|end|>
<|user|>
{Prompt) <|end|>
<|assistant|>
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name_or_path = "thesven/Phi-nut-Butter-Codebagel-v1-GPTQ"
tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True)
model = AutoModelForCausalLM.from_pretrained(
model_name_or_path,
device_map="auto",
trust_remote_code=False,
revision="main",
)
model.pad_token = model.config.eos_token_id
prompt_template = '''
<|system|>
You are an expert developer. Please help me with any coding questions.<|end|>
<|user|>
In typescript how would I use a function that looks like this <T>(config:T):T<|end|>
<|assistant|>
'''
input_ids = tokenizer(prompt_template, return_tensors='pt').input_ids.cuda()
output = model.generate(inputs=input_ids, temperature=0.1, do_sample=True, top_p=0.95, top_k=40, max_new_tokens=256)
generated_text = tokenizer.decode(output[0, len(input_ids[0]):], skip_special_tokens=True)
display(generated_text)