|
--- |
|
tags: |
|
- autotrain |
|
- text-generation |
|
- mistral |
|
- fine-tune |
|
- text-generation-inference |
|
- chat |
|
- Trained with Auto-train |
|
- pytorch |
|
widget: |
|
- text: 'I love AutoTrain because ' |
|
license: apache-2.0 |
|
language: |
|
- en |
|
library_name: transformers |
|
pipeline_tag: text-generation |
|
--- |
|
|
|
# Model Trained Using AutoTrain |
|
|
|
 |
|
|
|
The mistral-7b-fraud2-finetuned Large Language Model (LLM) is a fine-tuned version of the [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) generative text model using a variety of synthetically generated Fraudulent transcripts datasets. |
|
|
|
For full details of this model please read [release blog post](https://mistral.ai/news/announcing-mistral-7b/) |
|
|
|
## Instruction format |
|
|
|
In order to leverage instruction fine-tuning, your prompt should be surrounded by `[INST]` and `[\INST]` tokens. The very first instruction should begin with a begin of sentence id. The next instructions should not. The assistant generation will be ended by the end-of-sentence token id. |
|
|
|
E.g. |
|
|
|
```python |
|
from transformers import AutoModelForCausalLM, AutoTokenizer |
|
|
|
device = "cuda" # the device to load the model onto |
|
|
|
model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1") |
|
tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1") |
|
|
|
text = "<s>[INST] Below is a conversation transcript [/INST]" |
|
"Your credit card has been stolen, and you need to contact us to resolve the issue. We will help you protect your information and prevent further fraud.</s> " |
|
"[INST] Analyze the conversation and determine if it's fraudulent or legitimate. [/INST]" |
|
|
|
encodeds = tokenizer(text, return_tensors="pt", add_special_tokens=False) |
|
|
|
model_inputs = encodeds.to(device) |
|
model.to(device) |
|
|
|
generated_ids = model.generate(**model_inputs, max_new_tokens=1000, do_sample=True) |
|
decoded = tokenizer.batch_decode(generated_ids) |
|
print(decoded[0]) |
|
``` |
|
|
|
## Model Architecture |
|
This instruction model is based on Mistral-7B-v0.1, a transformer model with the following architecture choices: |
|
- Grouped-Query Attention |
|
- Sliding-Window Attention |
|
- Byte-fallback BPE tokenizer |
|
|
|
## The Team |
|
- BILIC TEAM OF AI ENGINEERS |
