|
--- |
|
base_model: meta-llama/Llama-3.1-8B |
|
library_name: peft |
|
license: llama3.1 |
|
language: |
|
- en |
|
tags: |
|
- finance |
|
--- |
|
|
|
# Model Card for Model ID |
|
|
|
<!-- Provide a quick summary of what the model is/does. --> |
|
|
|
|
|
|
|
## Model Details |
|
|
|
### Model Description |
|
|
|
<!-- Provide a longer summary of what this model is. --> |
|
|
|
|
|
|
|
- **Developed by:** [More Information Needed] |
|
- **Funded by [optional]:** [More Information Needed] |
|
- **Shared by [optional]:** [More Information Needed] |
|
- **Model type:** [More Information Needed] |
|
- **Language(s) (NLP):** [More Information Needed] |
|
- **License:** [More Information Needed] |
|
- **Finetuned from model [optional]:** [More Information Needed] |
|
|
|
### Model Sources [optional] |
|
|
|
<!-- Provide the basic links for the model. --> |
|
|
|
- **Repository:** [More Information Needed] |
|
- **Paper [optional]:** [More Information Needed] |
|
- **Demo [optional]:** [More Information Needed] |
|
|
|
## Uses |
|
|
|
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
|
|
|
### Direct Use |
|
|
|
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> |
|
|
|
```python |
|
from transformers import BitsAndBytesConfig, AutoModelForCausalLM, AutoTokenizer |
|
import torch |
|
from peft import PeftModel, PeftConfig |
|
from transformers import AutoModelForCausalLM, pipeline |
|
import logging |
|
# Suppress all warnings |
|
logging.getLogger("transformers").setLevel(logging.CRITICAL) #weird warning when using model for inference |
|
|
|
# Check if CUDA is available |
|
if torch.cuda.is_available(): |
|
num_devices = torch.cuda.device_count() |
|
print(f"Number of available CUDA devices: {num_devices}") |
|
|
|
for i in range(num_devices): |
|
device_name = torch.cuda.get_device_name(i) |
|
print(f"\nDevice {i}: {device_name}") |
|
else: |
|
print("CUDA is not available.") |
|
# Specify the device (0 for GPU or -1 for CPU) |
|
device = 0 if torch.cuda.is_available() else -1 |
|
|
|
config = PeftConfig.from_pretrained("smartinez1/Llama-3.1-8B-FINLLM") |
|
base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B") |
|
model = PeftModel.from_pretrained(base_model, "smartinez1/Llama-3.1-8B-FINLLM") |
|
# Load the tokenizer associated with the base model |
|
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.1-8B") |
|
# Define the unique padding token for fine-tuning |
|
custom_pad_token = "<|finetune_right_pad_id|>" |
|
tokenizer.add_special_tokens({'pad_token': custom_pad_token}) |
|
pad_token_id = tokenizer.pad_token_id |
|
|
|
# Set up the text generation pipeline with the PEFT model, specifying the device |
|
generator = pipeline("text-generation", model=model, tokenizer=tokenizer, device=device) |
|
|
|
# List of user inputs |
|
user_inputs = [ |
|
"Provide a link for Regulation A (Extensions of Credit by Federal Reserve Banks) law", |
|
"Define the following term: Insurance Scores.", |
|
"Expand the following acronym into its full form: ESCB.", |
|
"Provide a concise answer to the following question: Which countries currently have bilateral FTAs in effect with the U.S.?", |
|
"""Given the following text, only list the following for each: specific Organizations, Legislations, Dates, Monetary Values, |
|
and Statistics When can counterparties start notifying the national competent authorities (NCAs) of their intention to apply |
|
the reporting exemption in accordance with Article 9(1) EMIR, as amended by Regulation 2019/834?""", |
|
"Provide a concise answer to the following question: What type of license is the Apache License, Version 2.0?" |
|
] |
|
|
|
# Define the prompt template |
|
prompt_template = """Below is an instruction that describes a task. Write a response that appropriately completes the request. |
|
|
|
### Instruction: |
|
{} |
|
|
|
### Answer: |
|
""" |
|
|
|
# Loop over each user input and generate a response |
|
for user_input in user_inputs: |
|
# Format the user input into the prompt |
|
prompt = prompt_template.format(user_input) |
|
|
|
# Generate a response from the model |
|
response = generator(prompt, max_length=200, num_return_sequences=1, do_sample=True) |
|
|
|
# Extract and clean up the AI's response |
|
response_str = response[0]['generated_text'].split('### Answer:')[1].strip() |
|
cut_ind = response_str.find("#") # Remove extra information after the response |
|
response_str = response_str[:cut_ind].strip() if cut_ind != -1 else response_str |
|
|
|
# Display the AI's response |
|
print(f"User: {user_input}") |
|
print(f"AI: {response_str}") |
|
print("-" * 50) # Separator for clarity |
|
### Downstream Use [optional] |
|
|
|
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> |
|
|
|
[More Information Needed] |
|
|
|
### Out-of-Scope Use |
|
|
|
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> |
|
|
|
[More Information Needed] |
|
|
|
## Bias, Risks, and Limitations |
|
|
|
<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
|
|
|
[More Information Needed] |
|
|
|
### Recommendations |
|
|
|
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
|
|
|
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
|
|
|
## How to Get Started with the Model |
|
|
|
Use the code below to get started with the model. |
|
|
|
[More Information Needed] |
|
|
|
## Training Details |
|
|
|
### Training Data |
|
|
|
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
|
|
|
[More Information Needed] |
|
|
|
### Training Procedure |
|
|
|
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
|
|
|
#### Preprocessing [optional] |
|
|
|
[More Information Needed] |
|
|
|
|
|
#### Training Hyperparameters |
|
|
|
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
|
|
|
#### Speeds, Sizes, Times [optional] |
|
|
|
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> |
|
|
|
[More Information Needed] |
|
|
|
## Evaluation |
|
|
|
<!-- This section describes the evaluation protocols and provides the results. --> |
|
|
|
### Testing Data, Factors & Metrics |
|
|
|
#### Testing Data |
|
|
|
<!-- This should link to a Dataset Card if possible. --> |
|
|
|
[More Information Needed] |
|
|
|
#### Factors |
|
|
|
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> |
|
|
|
[More Information Needed] |
|
|
|
#### Metrics |
|
|
|
<!-- These are the evaluation metrics being used, ideally with a description of why. --> |
|
|
|
[More Information Needed] |
|
|
|
### Results |
|
|
|
[More Information Needed] |
|
|
|
#### Summary |
|
|
|
|
|
|
|
## Model Examination [optional] |
|
|
|
<!-- Relevant interpretability work for the model goes here --> |
|
|
|
[More Information Needed] |
|
|
|
## Environmental Impact |
|
|
|
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> |
|
|
|
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). |
|
|
|
- **Hardware Type:** [More Information Needed] |
|
- **Hours used:** [More Information Needed] |
|
- **Cloud Provider:** [More Information Needed] |
|
- **Compute Region:** [More Information Needed] |
|
- **Carbon Emitted:** [More Information Needed] |
|
|
|
## Technical Specifications [optional] |
|
|
|
### Model Architecture and Objective |
|
|
|
[More Information Needed] |
|
|
|
### Compute Infrastructure |
|
|
|
[More Information Needed] |
|
|
|
#### Hardware |
|
|
|
[More Information Needed] |
|
|
|
#### Software |
|
|
|
[More Information Needed] |
|
|
|
## Citation [optional] |
|
|
|
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
|
|
|
**BibTeX:** |
|
|
|
[More Information Needed] |
|
|
|
**APA:** |
|
|
|
[More Information Needed] |
|
|
|
## Glossary [optional] |
|
|
|
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> |
|
|
|
[More Information Needed] |
|
|
|
## More Information [optional] |
|
|
|
[More Information Needed] |
|
|
|
## Model Card Authors [optional] |
|
|
|
[More Information Needed] |
|
|
|
## Model Card Contact |
|
|
|
[More Information Needed] |
|
### Framework versions |
|
|
|
- PEFT 0.13.2 |
