Question Answering
Transformers
Safetensors
English
llama
text-generation
text-generation-inference
unsloth
ollama
mathematical-reasoning
Instructions to use NamrataThakur/llama31-8bn_SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NamrataThakur/llama31-8bn_SFT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="NamrataThakur/llama31-8bn_SFT")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("NamrataThakur/llama31-8bn_SFT") model = AutoModelForCausalLM.from_pretrained("NamrataThakur/llama31-8bn_SFT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
metadata
base_model: unsloth/meta-llama-3.1-8b-unsloth-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- ollama
- mathematical-reasoning
license: apache-2.0
language:
- en
datasets:
- openai/gsm8k
pipeline_tag: question-answering
Uploaded finetuned model
- Developed by: NamrataThakur
- License: apache-2.0
- Finetuned from model : unsloth/meta-llama-3.1-8b-unsloth-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
| Base Model | Fine-Tuning | Train Dataset | Validation Loss | Evaluation Dataset | Mean Answer Relevancy Score | Mean Answer Correctness Score |
|---|---|---|---|---|---|---|
| Llama3.1-8bn | Supervised Fine-Tuning | GSM8K | 1.12 | SmallThoughts | 0.736 | 0.437 |