Downloads · 30 days
11
17% of all-time downloads
ragler-mistral-7b
notoookay/ragler-mistral-7b
ragler-mistral-7b is a text generation model from notoookay. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
This model is a fine-tuned version of Mistral-7B using the RAG-LER (Retrieval Augmented Generation with LM-Enhanced Re-ranker) framework, as described in our paper.
All-time downloads
64
Public
Parameters
7.2B
14.5 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors14.5 GB · 100%
At a glance
- Task
- Text Generation
- Library
- transformers
- License
- mit
- Model type
- mistral
- Access
- Public
- Created
- Jul 25, 2024
- Updated
- Aug 8, 2024
- SHA
- d9c0cf4f
Try a prompt
Model card
From the Hugging Face model README
This model is a fine-tuned version of Mistral-7B using the RAG-LER (Retrieval Augmented Generation with LM-Enhanced Re-ranker) framework, as described in our paper.
How to Get Started with the Model
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
tokenizer = AutoTokenizer.from_pretrained("notoookay/ragler-mistral-7b")
model = AutoModelForCausalLM.from_pretrained("notoookay/ragler-mistral-7b", torch_dtype=torch.bfloat16, device_map="auto")
# Example usage
input_text = "### Instruction:\nAnswer the following question.\n\n### Input:\nQuestion:\nWhat is the capital of France?\n\n### Response:\n"
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0]))
- Task
- Text Generation
- Library
- transformers
- Type
- mistral
- License
- mit
- Created
- Jul 25, 2024
- Updated
- Aug 8, 2024