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Llama3_1_8B_Finance_QLoRA-GGUF
jhon53/Llama3_1_8B_Finance_QLoRA-GGUF
Llama3_1_8B_Finance_QLoRA-GGUF is a machine learning model from jhon53. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
language: en license: llama3 basemodel: meta-llama/Meta-Llama-3.1-8B-Instruct tags: - finance - sentiment-analysis - qlora - peft - lora datasets: - FinGPT/fingpt-sentiment-train metrics: - f1 - accuracy ---
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.gguf4.9 GB · 100%
At a glance
- Model type
- llama
- Access
- Public
- Created
- May 27, 2026
- Updated
- May 27, 2026
- SHA
- bcfc0bb5
Model card
From the Hugging Face model README
language: en license: llama3 base_model: meta-llama/Meta-Llama-3.1-8B-Instruct tags:
- finance
- sentiment-analysis
- qlora
- peft
- lora datasets:
- FinGPT/fingpt-sentiment-train metrics:
- f1
- accuracy
Llama-3.1-8B Financial Sentiment — QLoRA
LoRA adapters fine-tuned on FinGPT/fingpt-sentiment-train with QLoRA: 4-bit NF4 frozen base + bf16 LoRA adapters (r=16, alpha=32, dropout=0.05).
Task: 3-class financial sentiment — negative / neutral / positive
Evaluation Results
| Dataset | Base Accuracy | FT Accuracy | Base Macro-F1 | FT Macro-F1 |
|---|---|---|---|---|
| FPB in-domain | 0.8908 | 0.9748 | 0.8765 | 0.9725 |
| FiQA-SA OOD | 0.8120 | 0.9402 | 0.6705 | 0.8335 |
Baseline = zero-shot Meta-Llama-3.1-8B-Instruct with the same prompt template.
Quick Start
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = AutoModelForCausalLM.from_pretrained(
"meta-llama/Meta-Llama-3.1-8B-Instruct",
load_in_4bit=True,
device_map="auto",
)
model = PeftModel.from_pretrained(base, "jhon53/Llama3_1_8B_Finance_QLoRA")
tokenizer = AutoTokenizer.from_pretrained("jhon53/Llama3_1_8B_Finance_QLoRA")
Training Details
| Param | Value |
|---|---|
| Base model | meta-llama/Meta-Llama-3.1-8B-Instruct |
| Method | QLoRA (4-bit NF4 + LoRA bf16) |
| LoRA rank (r) | 16 |
| LoRA alpha | 32 |
| LoRA dropout | 0.05 |
| Target modules | q, k, v, o, gate, up, down projections |
| Training data | FinGPT/fingpt-sentiment-train (~76k) |
| Optimizer | AdamW 8-bit |
| Learning rate | 2e-4 (cosine schedule) |
| Epochs | 3 (early stopping, patience=3) |
| Loss | Completion-only cross-entropy |
Related Repos
- Merged 16-bit: jhon53/Llama3_1_8B_Finance_QLoRA-merged-16bit
- model: jhon53/Llama3_1_8B_Finance_QLoRA
tags:
- gguf
- llama.cpp
- unsloth
Llama3_1_8B_Finance_QLoRA-GGUF : GGUF
Example usage:
- For text only LLMs:
llama-cli -hf jhon53/Llama3_1_8B_Finance_QLoRA-GGUF --jinja - For multimodal models:
llama-mtmd-cli -hf jhon53/Llama3_1_8B_Finance_QLoRA-GGUF --jinja
Available Model files:
Meta-Llama-3.1-8B-Instruct.Q4_K_M.gguf
Ollama
An Ollama Modelfile is included for easy deployment.
- Type
- llama
- Created
- May 27, 2026
- Updated
- May 27, 2026