# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Q-bert/Terminis-7B")
model = AutoModelForCausalLM.from_pretrained("Q-bert/Terminis-7B")Quick Links
Terminis-7B
Merge v1olet/v1olet_marcoroni-go-bruins-merge-7B and mistralai/Mistral-7B-Instruct-v0.2 using slerp merge.
You can use ChatML and Alpaca format.
Open LLM Leaderboard Evaluation Results
Detailed results can be found Coming soon
| Metric | Value |
|---|---|
| Avg. | Coming soon |
| ARC (25-shot) | Coming soon |
| HellaSwag (10-shot) | Coming soon |
| MMLU (5-shot) | Coming soon |
| TruthfulQA (0-shot) | Coming soon |
| Winogrande (5-shot) | Coming soon |
| GSM8K (5-shot) | Coming soon |
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Q-bert/Terminis-7B")