Model Card for Model ID

Just only a text gen model type, I'm just test train my dataset and...it's work, very nice, try it.

Model Details

Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub.

Developed by: HuyRemy
Funded by : HuyRemy
Shared by : HuyRemy
Model type: Megatron Mistral
License: [email protected]

Model Demo:

Demo : https://ai.matilda.vn

Uses

USE T4 GPU

!pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
!pip install --no-deps xformers trl peft accelerate bitsandbytes

Direct Use

from unsloth import FastLanguageModel
import torch
max_seq_length = 2048
dtype = None 
load_in_4bit = True 
alpaca_prompt = """
### Instruction:
{}

### Input:
{}

### Response:
{}"""


def formatting_prompts_func(examples):
    instructions = examples["instruction"]
    inputs       = examples["input"]
    outputs      = examples["output"]
    texts = []
    for instruction, input, output in zip(instructions, inputs, outputs):
        text = alpaca_prompt.format(instruction, input, output) + EOS_TOKEN
        texts.append(text)
    return { "text" : texts, }
pass

model, tokenizer = FastLanguageModel.from_pretrained(
    model_name = "huyremy/aichat", 
    max_seq_length = max_seq_length,
    dtype = dtype,
    load_in_4bit = load_in_4bit,
)
FastLanguageModel.for_inference(model) 

EOS_TOKEN = tokenizer.eos_token 

inputs = tokenizer(
[
    alpaca_prompt.format(
        "who is Nguyễn Phú Trọng?", 
        "", 
        "", 
    ),
], return_tensors = "pt").to("cuda")

outputs = model.generate(**inputs, max_new_tokens = 64, use_cache = True)
tokenizer.batch_decode(outputs)

Model Card Contact

[email protected]