It remain factual and reliable even in dramatic situations.
Model Card for kevin009/llamaRAGdrama
Model Details
- Model Name: kevin009/llamaRAGdrama
- Model Type: Fine-tuned for Q&A, RAG.
- Fine-tuning Objective: Synthesis text content in Q&A, RAG scenarios.
Intended Use
- Applications: RAG, Q&A
Training Data
- Sources: Includes a diverse dataset of dramatic texts, enriched with factual databases and reliable sources to train the model on generating content that remains true to real-world facts.
- Preprocessing: In addition to removing non-content text, data was annotated to distinguish between purely creative elements and those that require factual accuracy, ensuring a balanced training approach.
How to Use
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("kevin009/llamaRAGdrama")
model = AutoModelForCausalLM.from_pretrained("kevin009/llamaRAGdrama")
input_text = "Enter your prompt here"
input_tokens = tokenizer.encode(input_text, return_tensors='pt')
output_tokens = model.generate(input_tokens, max_length=100, num_return_sequences=1, temperature=0.9)
generated_text = tokenizer.decode(output_tokens[0], skip_special_tokens=True)
print(generated_text)
Replace "Enter your prompt here"
with your starting text. Adjust temperature
for creativity level.
Limitations and Biases
- Content Limitation: While designed to be truthful, It may not be considered safe.
- Biases: It may remain biases and inaccurate.
Licensing and Attribution
- License: Apache-2.0
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 74.65 |
AI2 Reasoning Challenge (25-Shot) | 72.01 |
HellaSwag (10-Shot) | 88.83 |
MMLU (5-Shot) | 64.50 |
TruthfulQA (0-shot) | 70.24 |
Winogrande (5-shot) | 86.66 |
GSM8k (5-shot) | 65.66 |
- Downloads last month
- 5,130
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Spaces using kevin009/llamaRAGdrama 5
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard72.010
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard88.830
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.500
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard70.240
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard86.660
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard65.660