You can deploy this model and start earning money today!

RichardErkhov/
recoilme_-_Gemma-2-Ataraxy-Gemmasutra-9B-slerp-gguf

Name: recoilme_-_Gemma-2-Ataraxy-Gemmasutra-9B-slerp-gguf
Availability: InStock

Views

No views yet

Quantization made by Richard Erkhov.

Github

Discord

Request more models

Gemma-2-Ataraxy-Gemmasutra-9B-slerp - GGUF

Model creator: https://huggingface.co/recoilme/
Original model: https://huggingface.co/recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp/

Name	Quant method	Size
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q2_K.gguf	Q2_K	3.54GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.IQ3_XS.gguf	IQ3_XS	3.86GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.IQ3_S.gguf	IQ3_S	4.04GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q3_K_S.gguf	Q3_K_S	4.04GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.IQ3_M.gguf	IQ3_M	4.19GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q3_K.gguf	Q3_K	4.43GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q3_K_M.gguf	Q3_K_M	4.43GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q3_K_L.gguf	Q3_K_L	4.78GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.IQ4_XS.gguf	IQ4_XS	4.86GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q4_0.gguf	Q4_0	5.07GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.IQ4_NL.gguf	IQ4_NL	5.1GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q4_K_S.gguf	Q4_K_S	5.1GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q4_K.gguf	Q4_K	5.37GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q4_K_M.gguf	Q4_K_M	5.37GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q4_1.gguf	Q4_1	5.55GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q5_0.gguf	Q5_0	6.04GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q5_K_S.gguf	Q5_K_S	6.04GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q5_K.gguf	Q5_K	6.19GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q5_K_M.gguf	Q5_K_M	6.19GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q5_1.gguf	Q5_1	6.52GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q6_K.gguf	Q6_K	7.07GB
Gemma-2-Ataraxy-Gemmasutra-9B-slerp.Q8_0.gguf	Q8_0	9.15GB

Original model description:

license: apache-2.0 library_name: transformers model-index:

name: Gemma-2-Ataraxy-Gemmasutra-9B-slerp results:
- task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics:
  - type: inst_level_strict_acc and prompt_level_strict_acc value: 76.49 name: strict accuracy source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics:
  - type: acc_norm value: 42.25 name: normalized accuracy source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics:
  - type: exact_match value: 1.74 name: exact match source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics:
  - type: acc_norm value: 10.74 name: acc_norm source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics:
  - type: acc_norm value: 12.39 name: acc_norm source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics:
  - type: acc value: 35.63 name: accuracy source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp name: Open LLM Leaderboard

Gemma-2-Ataraxy-Gemmasutra-9B-slerp

💻 Usage

python

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "recoilme/Gemma-2-Ataraxy-Gemmasutra-9B-slerp"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	29.87
IFEval (0-Shot)	76.49
BBH (3-Shot)	42.25
MATH Lvl 5 (4-Shot)	1.74
GPQA (0-shot)	10.74
MuSR (0-shot)	12.39
MMLU-PRO (5-shot)	35.63

RichardErkhov/recoilme_-_Gemma-2-Ataraxy-Gemmasutra-9B-slerp-gguf

Original model description:

Gemma-2-Ataraxy-Gemmasutra-9B-slerp

💻 Usage

Open LLM Leaderboard Evaluation Results

RichardErkhov/
recoilme_-_Gemma-2-Ataraxy-Gemmasutra-9B-slerp-gguf