File size: 7,183 Bytes
5271eb4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 |
Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
Dracarys2-72B-Instruct - GGUF
- Model creator: https://huggingface.co/abacusai/
- Original model: https://huggingface.co/abacusai/Dracarys2-72B-Instruct/
| Name | Quant method | Size |
| ---- | ---- | ---- |
| [Dracarys2-72B-Instruct.Q2_K.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/blob/main/Dracarys2-72B-Instruct.Q2_K.gguf) | Q2_K | 27.76GB |
| [Dracarys2-72B-Instruct.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/blob/main/Dracarys2-72B-Instruct.IQ3_XS.gguf) | IQ3_XS | 30.59GB |
| [Dracarys2-72B-Instruct.IQ3_S.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/blob/main/Dracarys2-72B-Instruct.IQ3_S.gguf) | IQ3_S | 32.12GB |
| [Dracarys2-72B-Instruct.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/blob/main/Dracarys2-72B-Instruct.Q3_K_S.gguf) | Q3_K_S | 32.12GB |
| [Dracarys2-72B-Instruct.IQ3_M.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/blob/main/Dracarys2-72B-Instruct.IQ3_M.gguf) | IQ3_M | 33.07GB |
| [Dracarys2-72B-Instruct.Q3_K.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/blob/main/Dracarys2-72B-Instruct.Q3_K.gguf) | Q3_K | 35.11GB |
| [Dracarys2-72B-Instruct.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/blob/main/Dracarys2-72B-Instruct.Q3_K_M.gguf) | Q3_K_M | 29.28GB |
| [Dracarys2-72B-Instruct.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/blob/main/Dracarys2-72B-Instruct.Q3_K_L.gguf) | Q3_K_L | 36.79GB |
| [Dracarys2-72B-Instruct.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/blob/main/Dracarys2-72B-Instruct.IQ4_XS.gguf) | IQ4_XS | 7.05GB |
| [Dracarys2-72B-Instruct.Q4_0.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/tree/main/) | Q4_0 | 38.4GB |
| [Dracarys2-72B-Instruct.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/tree/main/) | IQ4_NL | 38.9GB |
| [Dracarys2-72B-Instruct.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/tree/main/) | Q4_K_S | 40.88GB |
| [Dracarys2-72B-Instruct.Q4_K.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/tree/main/) | Q4_K | 44.16GB |
| [Dracarys2-72B-Instruct.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/tree/main/) | Q4_K_M | 44.16GB |
| [Dracarys2-72B-Instruct.Q4_1.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/tree/main/) | Q4_1 | 42.56GB |
| [Dracarys2-72B-Instruct.Q5_0.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/tree/main/) | Q5_0 | 46.72GB |
| [Dracarys2-72B-Instruct.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/tree/main/) | Q5_K_S | 47.85GB |
| [Dracarys2-72B-Instruct.Q5_K.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/tree/main/) | Q5_K | 50.71GB |
| [Dracarys2-72B-Instruct.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/tree/main/) | Q5_K_M | 50.71GB |
| [Dracarys2-72B-Instruct.Q5_1.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/blob/main/Dracarys2-72B-Instruct.Q5_1.gguf) | Q5_1 | 34.61GB |
| [Dracarys2-72B-Instruct.Q6_K.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/tree/main/) | Q6_K | 59.93GB |
| [Dracarys2-72B-Instruct.Q8_0.gguf](https://huggingface.co/RichardErkhov/abacusai_-_Dracarys2-72B-Instruct-gguf/tree/main/) | Q8_0 | 71.96GB |
Original model description:
---
language:
- en
license: other
tags:
- chat
license_name: tongyi-qianwen
license_link: https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE
pipeline_tag: text-generation
---
# Dracarys2-72B-Instruct
# Introduction
We introduce the latest in the Smaug series, the Dracarys family of finetunes targeting coding performance improvements
across a variety of base models.
This variant is a finetune of [Qwen2.5-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct)
Compared to Qwen2.5-72B-Instruct, Dracarys has better LiveCodeBench scores (see evaluation results below).
### Model Description
- **Developed by:** [Abacus.AI](https://abacus.ai)
- **License:** https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE
- **Finetuned from model:** [Qwen2.5-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct).
## How to use
The prompt format is unchanged from Qwen2.5-72B-Instruct (see evaluations for prompt details for LCB)
### Use with transformers
See the snippet below for usage with Transformers:
```python
import transformers
import torch
model_id = "abacusai/Dracarys2-72B-Instruct"
pipeline = transformers.pipeline(
"text-generation",
model=model_id,
model_kwargs={"torch_dtype": torch.bfloat16},
device_map="auto",
)
messages = [
{"role": "system", "content": "You are data science coding assistant that generates Python code using Pandas and Numpy."},
{"role": "user", "content": "Write code to select rows from the dataframe `df` having the maximum `temp` for each `city`"},
]
prompt = pipeline.tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
terminators = [
pipeline.tokenizer.eos_token_id,
pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
]
outputs = pipeline(
prompt,
max_new_tokens=256,
eos_token_id=terminators,
do_sample=True,
temperature=0.6,
top_p=0.9,
)
print(outputs[0]["generated_text"][len(prompt):])
```
# Evaluation Results
## LiveCodeBench
| Model | Code Generation | Code Execution (COT) |Test Output Prediction |
|----------------------------|-----------------|----------------------|-----------------------|
| **Dracarys2-72B-Instruct** | **53.80** | **89.12** | **59.61** |
| Qwen2.5-72B-Instruct | 53.03 | 88.72 | 46.28 |
## Breakdown of LiveCodeBench CodeGeneration
| Model | Easy | Medium | Hard |
|---------------------------|-----------------|----------------|---------------|
| **Dracarys2-72B-Instruct**| **88.79** | **50.28** | 9.47 |
| Qwen2.5-72B-Instruct | 86.99 | 49.59 | 9.99 |
## Breakdown of LiveCodeBench TestOutputPrediction
| Model | Easy | Medium | Hard |
|---------------------------|-----------------|----------------|-----------------------|
| **Dracarys2-72B-Instruct**| **79.25** | **53.76** | **37.63** |
| Qwen2.5-72B-Instruct | 68.43 | 39.46 | 22.22 |
|