File size: 1,968 Bytes
5920aca d9b7eb7 5920aca |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 |
---
license: apache-2.0
datasets:
- motexture/cData
language:
- en
base_model:
- HuggingFaceTB/SmolLM2-1.7B-Instruct
pipeline_tag: text-generation
tags:
- smoll
- coding
- coder
- model
- small
---
# SmolLCoder-1.7B-Instruct
## Introduction
SmolLCoder-1.7B-Instruct is a fine-tuned version of SmolLM2-1.7B-Instruct, trained on the cData coding dataset.
## Quickstart
Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
device = "cuda" # the device to load the model onto
model = AutoModelForCausalLM.from_pretrained(
"motexture/SmolLCoder-1.7B-Instruct",
torch_dtype="auto",
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("motexture/SmolLCoder-1.7B-Instruct")
prompt = "Write a C++ program that prints Hello World!"
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": prompt}
]
text = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
model_inputs = tokenizer([text], return_tensors="pt").to(device)
generated_ids = model.generate(
model_inputs.input_ids,
max_new_tokens=4096,
do_sample=True,
temperature=0.3
)
generated_ids = [
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
]
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
```
## License
[Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)
## Citation
```bash
@misc{allal2024SmolLM2,
title={SmolLM2 - with great data, comes great performance},
author={Loubna Ben Allal and Anton Lozhkov and Elie Bakouch and Gabriel Martín Blázquez and Lewis Tunstall and Agustín Piqueres and Andres Marafioti and Cyril Zakka and Leandro von Werra and Thomas Wolf},
year={2024},
}
``` |