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RichardErkhov/
Weyaxi_-_Seraph-7B-gguf

Name: Weyaxi_-_Seraph-7B-gguf
Availability: InStock

endpoints_compatible

gguf

template

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Quantization made by Richard Erkhov.

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Seraph-7B - GGUF

Model creator: https://huggingface.co/Weyaxi/
Original model: https://huggingface.co/Weyaxi/Seraph-7B/

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

Original model description:

license: cc-by-nc-4.0 model-index:

name: Seraph-7B 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: 67.83 name: normalized accuracy source: url: >- https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Seraph-7B 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: 86.22 name: normalized accuracy source: url: >- https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Seraph-7B 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: 65.07 name: accuracy source: url: >- https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Seraph-7B 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: 59.49 source: url: >- https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Seraph-7B 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: 80.66 name: accuracy source: url: >- https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Seraph-7B 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: 71.87 name: accuracy source: url: >- https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Seraph-7B name: Open LLM Leaderboard tags:
merge

Seraph-7B

This is the model for Seraph-7B. I used mergekit to merge models.

Prompt Templates

You can use these prompt templates, but I recommend using ChatML.

ChatML:

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

System, User, Asistant Alpaca Style:

### System:
{system}
### User:
{user}
### Assistant:

Yaml Config

yaml

slices:
  - sources:
      - model: Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp
        layer_range: [0, 32]
      - model: Q-bert/MetaMath-Cybertron-Starling
        layer_range: [0, 32]
merge_method: slerp
base_model: mistralai/Mistral-7B-v0.1
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5 # fallback for rest of tensors
dtype: bfloat16

Quantizationed versions

Quantizationed versions of this model is available thanks to TheBloke.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	71.86
ARC (25-shot)	67.83
HellaSwag (10-shot)	86.22
MMLU (5-shot)	65.07
TruthfulQA (0-shot)	59.49
Winogrande (5-shot)	80.66
GSM8K (5-shot)	71.87

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RichardErkhov/Weyaxi_-_Seraph-7B-gguf