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ABX-AI/phi-2-orange-v2-GGUF-IQ-Imatrix
phi-2-orange-v2-GGUF-IQ-Imatrix is a machine learning model from ABX-AI. 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 mit.
I like the Phi-2 variants, and noticed there isn't a single repo that offers GGUF with a full range of sizes. I quantized this model for myself, but also for anyone else interested. It includes a good variety of small…
Downloads · 30 days
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From the Hugging Face model README
I like the Phi-2 variants, and noticed there isn't a single repo that offers GGUF with a full range of sizes. I quantized this model for myself, but also for anyone else interested. It includes a good variety of small quants + Q6_K, Q8_0, F16 + Imatrix.

A two-step finetune of Phi-2, with a bit more zest.
This is an improved version of the original Phi-2-Orange that uses an updated training process on the same datasets.
It also uses the latest updated model from Microsoft's Phi-2, making it directly usable within Hugging Face's Transformers library (without the need for trust remote code).
Phi-2 Orange v2 uses ChatML as the prompt format.
(Update 12th March 2024: fixed eos_token issue)
It's recommended to always prompt with a system instruction (use whatever system prompt you like):
<|im_start|>system
You are a helpful assistant for Python which outputs in Markdown format.<|im_end|>
<|im_start|>user
Write a function to calculate the Fibonacci sequence<|im_end|>
<|im_start|>assistant
For example, if you find the model's output to be overly verbose, instruct it to be short and concise:
<|im_start|>system
You are a helpful assistant. Be short and direct in your answers.<|im_end|>
<|im_start|>user
Was Tom Hanks in the movie Forrest Gump? If so, who did he play and give details of the plot.<|im_end|>
<|im_start|>assistant
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Average | 63.67 |
| AI2 Reasoning Challenge (25-Shot) | 61.86 |
| HellaSwag (10-Shot) | 76.32 |
| MMLU (5-Shot) | 55.72 |
| TruthfulQA (0-shot) | 54.84 |
| Winogrande (5-shot) | 75.69 |
| GSM8k (5-shot) | 57.62 |
YALL - Yet Another LLM Leaderboard
Evaluation from mlabonne's alternative LLM leaderboard:
| Metric | Value |
|---|---|
| Average | 49.64 |
| AGIEval | 34.55 |
| GPT4All | 70.96 |
| TruthfulQA | 54.87 |
| Bigbench | 38.17 |
This model shares the same limitations as the underlying Phi-2 model, details of which are found here.