Hugging Face's logo

smartinez1
/
Llama-3.1-8B-FINLLM

PEFT
Safetensors
English
finance
Model card Files
xet
Community
Llama-3.1-8B-FINLLM / README.md
smartinez1's picture
smartinez1
Update README.md
9fa8017 verified
preview code
|
raw
history blame
7.1 kB
metadata
base_model: meta-llama/Llama-3.1-8B
library_name: peft
license: llama3.1
language:
  - en
tags:
  - finance

Model Card for Model ID

Model Details

Model Description

  • 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]

  • Repository: [More Information Needed]
  • Paper [optional]: [More Information Needed]
  • Demo [optional]: [More Information Needed]

Uses

Direct Use 


from huggingface_hub import login
from transformers import BitsAndBytesConfig, AutoModelForCausalLM, AutoTokenizer
import torch
from peft import PeftModel, PeftConfig
from transformers import AutoModelForCausalLM, pipeline


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")

# 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 Credit Card Accountability Responsibility and Disclosure Act law.",
    "Define the following term: National Automated Clearing House Association.",
    "Expand the following acronym into its full form: CIA."
]

# Define the prompt template
prompt_template = """Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{0}

### Answer:
{1}
"""

# 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