Text Generation
PEFT
Safetensors
English
mistral
reasoning
legal-analysis
mathematical-reasoning
cognitive-architectures
large-language-model
logical-reasoning
lora
vanta-research
apollo
collaborative
frontier
mistral-ai
conversational
conversational-ai
chat
ai-research
ai-alignment-research
ai-alignment
ai-behavior
ai-behavior-research
Instructions to use vanta-research/apollo-v1-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vanta-research/apollo-v1-7b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3") model = PeftModel.from_pretrained(base_model, "vanta-research/apollo-v1-7b") - Notebooks
- Google Colab
- Kaggle
๐ Apollo V1 7B: Advanced Reasoning Language Model - Complete model release with LoRA fine-tuned Mistral-7B-Instruct-v0.2, 161M parameter adapter, Apache 2.0 license, and professional documentation for logical, mathematical, and legal reasoning
a2897eb verified Download tokenizer.json from vanta-research/apollo-v1-7b: direct link, hf CLI and curl.
- Browser
- Download file 3.67 MB
-
https://huggingface.co/vanta-research/apollo-v1-7b/resolve/main/tokenizer.json
- Command line
-
hf download hf://vanta-research/apollo-v1-7b/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/vanta-research/apollo-v1-7b/resolve/main/tokenizer.json
3.67 MB
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