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Qwen-2-Refueled
refuelai/Qwen-2-Refueled
Qwen-2-Refueled is a machine learning model from refuelai. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as cc-by-nc-4.0.
<div style="width: auto; margin-left: auto; margin-right: auto; background-color:black" <img src="https://assets-global.website-files.com/6423879a8f63c1bb18d74bfa/648818d56d04c3bdf36d71abRefuelrev8-01ts-p-1600.png" al…
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At a glance
- License
- cc-by-nc-4.0
- Model type
- qwen2
- Access
- Public
- Created
- Jan 8, 2025
- Updated
- Jan 8, 2025
- SHA
- 9cd3bca2
Base models
Model card
From the Hugging Face model README
<div style="width: auto; margin-left: auto; margin-right: auto; background-color:black">
<img src="https://assets-global.website-files.com/6423879a8f63c1bb18d74bfa/648818d56d04c3bdf36d71ab_Refuel_rev8-01_ts-p-1600.png" alt="Refuel.ai" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
Model Details
RefuelLLM-2-mini, aka Qwen-2-Refueled, is a Qwen-2-1.5B base model instruction tuned on a corpus of 2750+ datasets, spanning tasks such as classification, reading comprehension, structured attribute extraction and entity resolution. We're excited to open-source the model for the community to build on top of.
More details about RefuelLLM-2-mini, and the RefuelLLM-2 family of models.
Model developers - Refuel AI
Input - Text only.
Output - Text only.
Architecture - Qwen-2-Refueled is built on top of a Qwen-2-1.5B base model.
Release Date - Jan 8, 2025.
License - CC BY-NC 4.0
How to use
This repository contains weights for Qwen-2-Refueled that are compatible for use with HuggingFace. See the snippet below for usage with Transformers:
>>> import torch
>>> from transformers import AutoModelForCausalLM, AutoTokenizer
>>> model_id = "refuelai/Qwen-2-Refueled"
>>> tokenizer = AutoTokenizer.from_pretrained(model_id)
>>> model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")
>>> messages = [{"role": "user", "content": "Is this comment toxic or non-toxic: RefuelLLM is the new way to label text data!"}]
>>> inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True).to("cuda")
>>> outputs = model.generate(inputs, max_new_tokens=20)
>>> print(tokenizer.decode(outputs[0]))
Benchmarks
In this section, we report the output quality results on our benchmark of labeling tasks. For details on the methodology see here.
| Model | Size | Overall | Classification | Reading Comprehension | Structure Extraction | Entity Matching |
|---|---|---|---|---|---|---|
| RefuelLLM-2-mini | 1.5B | 75.02% | 72.18% | 78.18% | 75.18% | 80.75% |
| Qwen-2-3B | 3B | 67.62% | 70.91% | 71.53% | 75.72% | 80.75% |
| Phi-3.5-mini-instruct | 3.8B | 65.63% | 70.57% | 71.89% | 65.34% | 83.53% |
| Gemma-2-2B | 2B | 64.52% | 67.99% | 67.94% | 76.01% | 39.50% |
| Llama-3-3B | 3B | 55.80% | 55.81% | 65.12% | 61.50% | 55.01% |
| Qwen-2-1.5B | 1.5B | 51.22% | 47.36% | 67.15% | 56.17% | 45.25% |
| Llama-3-1B | 1B | 39.92% | 44.58% | 29.67% | 39.50% | 62.94% |
Limitations
The Qwen-2-Refueled does not have any moderation mechanisms. We're looking forward to engaging with the community on ways to make the model finely respect guardrails, allowing for deployment in environments requiring moderated outputs.
- Type
- qwen2
- License
- cc-by-nc-4.0
- Created
- Jan 8, 2025
- Updated
- Jan 8, 2025