Mistral-7B
Collection
5 items • Updated • 1
Text Generation
Transformers
Safetensors
English
mistral
mergekit
Merge
roleplay
conversational
Eval Results (legacy)
text-generation-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("FallenMerick/Smart-Lemon-Cookie-7B")
model = AutoModelForCausalLM.from_pretrained("FallenMerick/Smart-Lemon-Cookie-7B")
messages = [
{"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
tokenize=True,
return_dict=True,
return_tensors="pt",
).to(model.device)
outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))Quick Links
image courtesy of @matchaaaaa
Smart-Lemon-Cookie-7B
This is a merge of pre-trained language models created using mergekit.
GGUF quants:
- https://huggingface.co/FaradayDotDev/Smart-Lemon-Cookie-7B-GGUF
- https://huggingface.co/mradermacher/Smart-Lemon-Cookie-7B-GGUF
Merge Details
Merge Method
This model was merged using the TIES merge method using MTSAIR/multi_verse_model as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
models:
- model: SanjiWatsuki/Silicon-Maid-7B
parameters:
density: 1.0
weight: 1.0
- model: SanjiWatsuki/Kunoichi-7B
parameters:
density: 0.4
weight: 1.0
- model: KatyTheCutie/LemonadeRP-4.5.3
parameters:
density: 0.6
weight: 1.0
merge_method: ties
base_model: MTSAIR/multi_verse_model
parameters:
normalize: true
dtype: float16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 68.16 |
| AI2 Reasoning Challenge (25-Shot) | 66.30 |
| HellaSwag (10-Shot) | 85.53 |
| MMLU (5-Shot) | 64.69 |
| TruthfulQA (0-shot) | 60.66 |
| Winogrande (5-shot) | 77.74 |
| GSM8k (5-shot) | 54.06 |
- Downloads last month
- 26
Model tree for FallenMerick/Smart-Lemon-Cookie-7B
Merge model
this model
Spaces using FallenMerick/Smart-Lemon-Cookie-7B 9
Collection including FallenMerick/Smart-Lemon-Cookie-7B
Paper for FallenMerick/Smart-Lemon-Cookie-7B
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard66.300
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard85.530
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.690
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard60.660
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard77.740
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard54.060
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="FallenMerick/Smart-Lemon-Cookie-7B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)