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RichardErkhov/
tlphams_-_zoyllm-7b-slimorca-gguf

Name: tlphams_-_zoyllm-7b-slimorca-gguf
Availability: InStock

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zoyllm-7b-slimorca - GGUF

Model creator: https://huggingface.co/tlphams/
Original model: https://huggingface.co/tlphams/zoyllm-7b-slimorca/

Name	Quant method	Size
zoyllm-7b-slimorca.Q2_K.gguf	Q2_K	2.53GB
zoyllm-7b-slimorca.IQ3_XS.gguf	IQ3_XS	2.81GB
zoyllm-7b-slimorca.IQ3_S.gguf	IQ3_S	2.96GB
zoyllm-7b-slimorca.Q3_K_S.gguf	Q3_K_S	2.95GB
zoyllm-7b-slimorca.IQ3_M.gguf	IQ3_M	3.06GB
zoyllm-7b-slimorca.Q3_K.gguf	Q3_K	3.28GB
zoyllm-7b-slimorca.Q3_K_M.gguf	Q3_K_M	3.28GB
zoyllm-7b-slimorca.Q3_K_L.gguf	Q3_K_L	3.56GB
zoyllm-7b-slimorca.IQ4_XS.gguf	IQ4_XS	3.67GB
zoyllm-7b-slimorca.Q4_0.gguf	Q4_0	3.83GB
zoyllm-7b-slimorca.IQ4_NL.gguf	IQ4_NL	3.87GB
zoyllm-7b-slimorca.Q4_K_S.gguf	Q4_K_S	3.86GB
zoyllm-7b-slimorca.Q4_K.gguf	Q4_K	4.07GB
zoyllm-7b-slimorca.Q4_K_M.gguf	Q4_K_M	4.07GB
zoyllm-7b-slimorca.Q4_1.gguf	Q4_1	4.24GB
zoyllm-7b-slimorca.Q5_0.gguf	Q5_0	4.65GB
zoyllm-7b-slimorca.Q5_K_S.gguf	Q5_K_S	4.65GB
zoyllm-7b-slimorca.Q5_K.gguf	Q5_K	4.78GB
zoyllm-7b-slimorca.Q5_K_M.gguf	Q5_K_M	4.78GB
zoyllm-7b-slimorca.Q5_1.gguf	Q5_1	5.07GB
zoyllm-7b-slimorca.Q6_K.gguf	Q6_K	5.53GB
zoyllm-7b-slimorca.Q8_0.gguf	Q8_0	7.17GB

Original model description:

language:

en license: cc-by-nc-sa-4.0 tags:
finetuned pipeline_tag: text-generation model-index:
name: zoyllm-7b-slimorca 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: 50.6 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=tlphams/zoyllm-7b-slimorca 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: 72.12 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=tlphams/zoyllm-7b-slimorca 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: 48.78 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=tlphams/zoyllm-7b-slimorca 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: 49.13 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=tlphams/zoyllm-7b-slimorca 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: 67.32 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=tlphams/zoyllm-7b-slimorca 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: 20.7 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=tlphams/zoyllm-7b-slimorca name: Open LLM Leaderboard

Model Card for ZoyLLM-7B-SlimOrca

The ZoyLLM-7B-SlimOrca Large Language Model (LLM) is a LoRA-finetuned generative text model with Mistral-7B-v0.1 is the base model. Mistral-7B-v0.1 outperforms Llama 2 13B on all benchmarks we tested.

1. Model Architecture

ZoyLLM-7B-SlimOrca is a transformer model, with the following architecture choices:

Grouped-Query Attention
Sliding-Window Attention
Byte-fallback BPE tokenizer

2. Datasets

Self-introduction (20 samples)
SlimOrca (100k samples random sampled)
EverythingLM v3

3. Template

We finetuned the model using a chatml template

<|im_start|>system
{system}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

4. Test examples

4.1. Self-introduction

<|im_start|>system
You are a large language model named ZoyLLM.<|im_end|>
<|im_start|>user
Who are you?<|im_end|>
<|im_start|>assistant
I am ZoyLLM, an AI created by Pham Tung Lam and Nguyen Duc Nhan to be helpful, friendly and to understand humans better.<|im_end|>

4.2. RAG testbench sample

<|im_start|>system
You are a large language model named ZoyLLM.<|im_end|>
<|im_start|>user
Stocks rallied Friday even after the release of stronger-than-expected U.S. jobs data and a major increase in Treasury yields.  The Dow Jones Industrial Average gained 195.12 points, or 0.76%, to close at 31,419.58. The S&P 500 added 1.59% at 4,008.50. The tech-heavy Nasdaq Composite rose 1.35%, closing at 12,299.68. The U.S. economy added 438,000 jobs in August, the Labor Department said. Economists polled by Dow Jones expected 273,000 jobs. However, wages rose less than expected last month.  Stocks posted a stunning turnaround on Friday, after initially falling on the stronger-than-expected jobs report. At its session low, the Dow had fallen as much as 198 points; it surged by more than 500 points at the height of the rally. The Nasdaq and the S&P 500 slid by 0.8% during their lowest points in the day.  Traders were unclear of the reason for the intraday reversal. Some noted it could be the softer wage number in the jobs report that made investors rethink their earlier bearish stance. Others noted the pullback in yields from the day’s highs. Part of the rally may just be to do a market that had gotten extremely oversold with the S&P 500 at one point this week down more than 9% from its high earlier this year.  Yields initially surged after the report, with the 10-year Treasury rate trading near its highest level in 14 years. The benchmark rate later eased from those levels, but was still up around 6 basis points at 4.58%.  'We’re seeing a little bit of a give back in yields from where we were around 4.8%. [With] them pulling back a bit, I think that’s helping the stock market,' said Margaret Jones, chief investment officer at Vibrant Industries Capital Advisors. 'We’ve had a lot of weakness in the market in recent weeks, and potentially some oversold conditions.'
Based on above information, answer this question as short as possible: What was the percentage in increase in the Nasdaq at closing?<|im_end|>
<|im_start|>assistant
The Nasdaq Composite rose 1.35% at closing.<|im_end|>

5. Troubleshooting

If you see the following error:

KeyError: 'mistral'

NotImplementedError: Cannot copy out of meta tensor; no data!

Ensure you are utilizing a stable version of Transformers, 4.34.0 or newer.

6. The Zoy AI Team

Pham Tung Lam, Nguyen Duc Nhan.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	51.44
AI2 Reasoning Challenge (25-Shot)	50.60
HellaSwag (10-Shot)	72.12
MMLU (5-Shot)	48.78
TruthfulQA (0-shot)	49.13
Winogrande (5-shot)	67.32
GSM8k (5-shot)	20.70

RichardErkhov/tlphams_-_zoyllm-7b-slimorca-gguf