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letxbe/
mistral-7b-v03-BoundingDocs-rephrased

Name: mistral-7b-v03-BoundingDocs-rephrased
Availability: InStock

text-generation-inference

endpoints_compatible

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Model Card for letxbe/mistral-7b-v03-BoundingDocs-rephrased

letxbe/mistral-7b-v03-BoundingDocs-rephrased is a fine-tuned Mistral-7B-v0.3 for the Document Question Answering task. It was trained on BoundingDocs using the rephrased version of the questions.

Model Details

Model Description

Developed by: LetXBe
Model Type: LLM
Languages: Multilingual
License: CC BY 4.0
Finetuned From: Mistral-7B-v0.3
Input Format: Text using custom prompt
Output Format: JSON

🚀 How to Use

Prompt

The model should be prompted with this prompt:

python

TEMPLATE_PROMPT = '''<|startdocument|>
{DOCUMENT}
<|enddocument|>

<|starttask|>
Answer the following question about the document:
Question: "{QUESTION}"
Answer completing the following format:

'''json
{"value": ""}
'''

<|endtask|>
'''

where DOCUMENT is the textual content of the document page.

Inference Example

python

from transformers import AutoTokenizer, AutoModelForCausalLM

# Load model and tokenizer
tokenizer = AutoTokenizer.from_pretrained("letxbe/mistral-7b-v03-BoundingDocs-rephrased")
model = AutoModelForCausalLM.from_pretrained("letxbe/mistral-7b-v03-BoundingDocs-rephrased")

# Encode input
input_text = "Your prompt"
inputs = tokenizer(input_text, return_tensors="pt")

# Generate response
outputs = model.generate(**inputs)

# Decode and print
print(tokenizer.decode(outputs[0], skip_special_tokens=True))