Update README.md

README.md

@@ -1,3 +1,69 @@
----
-license: cc-by-nc-4.0
----
+---
+license: cc-by-nc-4.0
+base_model:
+- Qwen/Qwen2-1.5B-Instruct
+tags:
+- data processing
+- slm
+---
+
+
+## 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](https://www.refuel.ai/blog-posts/refuel-llm-2-mini), and the [RefuelLLM-2 family of models](https://www.refuel.ai/blog-posts/announcing-refuel-llm-2). 
+
+**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** - May 8, 2024.
+
+**License** - [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/deed.en)
+
+## 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:
+
+```python
+>>> 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](https://www.refuel.ai/blog-posts/refuel-llm-2-mini).
+
+
+|      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.