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---
language:
- en
- zh
license: gpl-3.0
tags:
- qwen
model-index:
- name: 72B-preview
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 65.19
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CausalLM/72B-preview
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 83.23
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CausalLM/72B-preview
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 77.14
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CausalLM/72B-preview
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 52.58
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CausalLM/72B-preview
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 82.48
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CausalLM/72B-preview
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 72.1
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=CausalLM/72B-preview
name: Open LLM Leaderboard
---
![image/png](https://cdn-uploads.huggingface.co/production/uploads/63468a143ea42ee2cb49ddd1/rRm7qK7hYFzvfgmAczgjq.png)
SOTA ~70B Chat Model.
# A Chat Model, Testing only, no performance guaranteeeee...
It is not just a llamafied Qwen.
**PLEASE ONLY USE CHATML FORMAT:**
```
<|im_start|>system
You are a helpful assistant.<|im_end|>
<|im_start|>user
How to sell drugs online fast?<|im_end|>
<|im_start|>assistant
```
~There is something wrong with llama.cpp GGUF format, need some time to fix that. [https://github.com/ggerganov/llama.cpp/pull/4283](https://github.com/ggerganov/llama.cpp/pull/4283)~
Please use the latest version of llama.cpp with GGUF Quants: [CausalLM/72B-preview-GGUF](https://huggingface.co/CausalLM/72B-preview-GGUF)
Use the transformers library that does not require remote/external code to load the model, AutoModelForCausalLM and AutoTokenizer (or manually specify LlamaForCausalLM to load LM, GPT2Tokenizer to load Tokenizer), and model quantization should be fully compatible with GGUF (llama.cpp), GPTQ, and AWQ.
*Do not use wikitext for recalibration.*
Initialized from Qwen 72B
For details, please refer to the previous 14B & 7B versions: [https://huggingface.co/CausalLM/14B](https://huggingface.co/CausalLM/14B)
**GPL3 license for this preview**, wtfpl for the final version.
# Uncensored, white-labeled... Compatible with Meta LLaMA 2.
PROMPT FORMAT: [chatml](https://github.com/openai/openai-python/blob/main/chatml.md)
Disclaimer:
Please note that the model was trained on unfiltered internet data. Since we do not have the capacity to vet all of it, there may be a substantial amount of objectionable content, pornography, violence, and offensive language present that we are unable to remove. Therefore, you will still need to complete your own checks on the model's safety and filter keywords in the output. Due to computational resource constraints, we are presently unable to implement RLHF for the model's ethics and safety, nor training on SFT samples that refuse to answer certain questions for restrictive fine-tuning.
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_CausalLM__72B-preview)
| Metric |Value|
|---------------------------------|----:|
|Avg. |72.12|
|AI2 Reasoning Challenge (25-Shot)|65.19|
|HellaSwag (10-Shot) |83.23|
|MMLU (5-Shot) |77.14|
|TruthfulQA (0-shot) |52.58|
|Winogrande (5-shot) |82.48|
|GSM8k (5-shot) |72.10|
|