README.md

---
base_model: unsloth/mistral-7b-v0.3-bnb-4bit
language:
- en
- kg
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
- sft
datasets:
- wikimedia/wikipedia
- Svngoku/xP3x-Kongo
---

# Kongostral

Kongostral is a continious pretrained version of the mistral model (`Mistral v3`) on Kikongo Wikipedia Corpus and fine-tuned on Kikongo Translated text from xP3x using the alcapa format.
The goal of this model is to produce a SOTA model who can easily predict the next token on Kikongo sentences and produce instruction base text generation.

- **Developed by:** Svngoku
- **License:** apache-2.0
- **Finetuned from model :** unsloth/mistral-7b-v0.3-bnb-4bit


## Inference with Unsloth
```py
FastLanguageModel.for_inference(model) # Enable native 2x faster inference
inputs = tokenizer([
    alpaca_prompt.format(
        #"", # instruction
        "Inki bima ke salaka ba gâteau ya pomme ya nsungi ?", # instruction
        "", # output - leave this blank for generation!
    )],
    return_tensors="pt").to("cuda")

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

## Inference with Transformers 🤗

```sh
!pip install -q -U bitsandbytes
!pip install -q -U git+https://github.com/huggingface/transformers.git
!pip install -q -U git+https://github.com/huggingface/peft.git
!pip install -q -U git+https://github.com/huggingface/accelerate.git
```

```py
from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
import torch

quantization_config = BitsAndBytesConfig(
  load_in_4bit=True,
  bnb_4bit_compute_dtype=torch.bfloat16
)

tokenizer = AutoTokenizer.from_pretrained("Svngoku/kongostral")
model = AutoModelForCausalLM.from_pretrained("Svngoku/kongostral", quantization_config=quantization_config)

prompt = "Inki kele Nsangu ya kisika yai ?"

model_inputs = tokenizer([prompt], return_tensors="pt").to("cuda")

generated_ids = model.generate(**model_inputs, max_new_tokens=500, do_sample=True)
tokenizer.batch_decode(generated_ids)[0]

```


## Observation

The model may produce results that are not accurate as requested by the user.
There is still work to be done to align and get more accurate results.

### Note
This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.

[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)