|
--- |
|
library_name: transformers |
|
base_model: unsloth/tinyllama-bnb-4bit |
|
license: mit |
|
datasets: |
|
- yahma/alpaca-cleaned |
|
language: |
|
- en |
|
pipeline_tag: text-generation |
|
tags: |
|
- Instruct |
|
- TinyLlama |
|
--- |
|
|
|
# Steps to try the model: |
|
|
|
### prompt Template |
|
```python |
|
alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. |
|
|
|
### Instruction: |
|
{} |
|
|
|
### Input: |
|
{} |
|
|
|
### Response: |
|
{}""" |
|
``` |
|
### load the model |
|
|
|
```python |
|
from transformers import AutoTokenizer, AutoModelForCausalLM |
|
|
|
tokenizer = AutoTokenizer.from_pretrained("damerajee/tinyllama-sft-small-v2") |
|
model = AutoModelForCausalLM.from_pretrained("damerajee/tinyllama-sft-small-v2") |
|
``` |
|
### Inference |
|
|
|
```python |
|
inputs = tokenizer( |
|
[ |
|
alpaca_prompt.format( |
|
"best places to visit in india", # instruction |
|
"", # input |
|
"", # output |
|
) |
|
]*1, return_tensors = "pt") |
|
|
|
outputs = model.generate(**inputs, max_new_tokens = 128, use_cache = True) |
|
tokenizer.batch_decode(outputs) |
|
``` |
|
|
|
|
|
|
|
# Model Information |
|
The base model [unsloth/tinyllama-bnb-4bit](https://huggingface.co/unsloth/tinyllama-bnb-4bit) was Instruct finetuned using [Unsloth](https://github.com/unslothai/unsloth) |
|
|
|
# Model Limitations |
|
The model was trained on a very small dataset so it might not be as good ,will be training on larger dataset soon |
|
# Training Details |
|
The model was trained for 1 epoch on a free goggle colab which took about 1 hour and 30 mins approximately |
