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RichardErkhov/
ResplendentAI_-_Datura_7B-gguf

Name: ResplendentAI_-_Datura_7B-gguf
Availability: InStock

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gguf

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Datura_7B - GGUF

Model creator: https://huggingface.co/ResplendentAI/
Original model: https://huggingface.co/ResplendentAI/Datura_7B/

Name	Quant method	Size
Datura_7B.Q2_K.gguf	Q2_K	2.53GB
Datura_7B.IQ3_XS.gguf	IQ3_XS	2.81GB
Datura_7B.IQ3_S.gguf	IQ3_S	2.96GB
Datura_7B.Q3_K_S.gguf	Q3_K_S	2.95GB
Datura_7B.IQ3_M.gguf	IQ3_M	3.06GB
Datura_7B.Q3_K.gguf	Q3_K	3.28GB
Datura_7B.Q3_K_M.gguf	Q3_K_M	3.28GB
Datura_7B.Q3_K_L.gguf	Q3_K_L	3.56GB
Datura_7B.IQ4_XS.gguf	IQ4_XS	3.67GB
Datura_7B.Q4_0.gguf	Q4_0	3.83GB
Datura_7B.IQ4_NL.gguf	IQ4_NL	3.87GB
Datura_7B.Q4_K_S.gguf	Q4_K_S	3.86GB
Datura_7B.Q4_K.gguf	Q4_K	4.07GB
Datura_7B.Q4_K_M.gguf	Q4_K_M	4.07GB
Datura_7B.Q4_1.gguf	Q4_1	4.24GB
Datura_7B.Q5_0.gguf	Q5_0	4.65GB
Datura_7B.Q5_K_S.gguf	Q5_K_S	4.65GB
Datura_7B.Q5_K.gguf	Q5_K	4.78GB
Datura_7B.Q5_K_M.gguf	Q5_K_M	4.78GB
Datura_7B.Q5_1.gguf	Q5_1	5.07GB
Datura_7B.Q6_K.gguf	Q6_K	5.53GB
Datura_7B.Q8_0.gguf	Q8_0	7.17GB

Original model description:

language:

en license: cc-by-sa-4.0 library_name: transformers datasets:
unalignment/toxic-dpo-v0.2
ResplendentAI/Synthetic_Soul_1k model-index:
name: Datura_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: 72.1 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ResplendentAI/Datura_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: 88.27 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ResplendentAI/Datura_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: 64.15 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ResplendentAI/Datura_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: 71.03 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ResplendentAI/Datura_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: 84.53 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ResplendentAI/Datura_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: 65.58 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ResplendentAI/Datura_7B name: Open LLM Leaderboard

Datura 7B

Flora with a bit of toxicity.

I've been making progress with my collection of tools, so I thought maybe I'd try something a little more toxic for this space. This should make for a more receptive model with fewer refusals.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	74.28
AI2 Reasoning Challenge (25-Shot)	72.10
HellaSwag (10-Shot)	88.27
MMLU (5-Shot)	64.15
TruthfulQA (0-shot)	71.03
Winogrande (5-shot)	84.53
GSM8k (5-shot)	65.58

RichardErkhov/ResplendentAI_-_Datura_7B-gguf

Original model description:

Datura 7B

Open LLM Leaderboard Evaluation Results

RichardErkhov/
ResplendentAI_-_Datura_7B-gguf