YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Quantization made by Richard Erkhov.
StrangeMerges_53-7B-model_stock - bnb 8bits
- Model creator: https://huggingface.co/Gille/
- Original model: https://huggingface.co/Gille/StrangeMerges_53-7B-model_stock/
Original model description:
license: apache-2.0 tags: - merge - mergekit - lazymergekit model-index: - name: StrangeMerges_53-7B-model_stock 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: 72.78 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_53-7B-model_stock 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: 88.46 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_53-7B-model_stock 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: 64.97 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_53-7B-model_stock 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: 73.86 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_53-7B-model_stock 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: 83.66 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_53-7B-model_stock 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: 72.71 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_53-7B-model_stock name: Open LLM Leaderboard
StrangeMerges_53-7B-model_stock
StrangeMerges_53-7B-model_stock is a merge of the following models using LazyMergekit:
馃З Configuration
models:
- model: Gille/StrangeMerges_52-7B-dare_ties
- model: rwitz/experiment26-truthy-iter-0
- model: Gille/StrangeMerges_32-7B-slerp
- model: AurelPx/Percival_01-7b-slerp
- model: Kukedlc/NeuralMaths-Experiment-7b
merge_method: model_stock
base_model: Gille/StrangeMerges_52-7B-dare_ties
dtype: bfloat16
馃捇 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Gille/StrangeMerges_53-7B-model_stock"
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. | 76.07 |
| AI2 Reasoning Challenge (25-Shot) | 72.78 |
| HellaSwag (10-Shot) | 88.46 |
| MMLU (5-Shot) | 64.97 |
| TruthfulQA (0-shot) | 73.86 |
| Winogrande (5-shot) | 83.66 |
| GSM8k (5-shot) | 72.71 |
- Downloads last month
- 1
Inference Providers NEW
This model isn't deployed by any Inference Provider. 馃檵 Ask for provider support