Create README.md

README.md

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+---
+tags:
+- llama2
+---
+
+## Model Details
+
+### Model Description
+
+
+We have followed up on our previous training runs related to extending the context length
+of Llama models. The associated github repository 
+
+https://github.com/abacusai/long-context
+
+has some basic details on our approach and metrics. We have also published a paper on arXiv
+that covers our experiments and analysis a lot more comprehensively.
+
+http://arxiv.org/abs/2308.10882
+
+- **Developed by:** [Abacus.AI](https://abacus.ai)
+- **Model type:** Transformer based autoregressive causal language model
+- **License:** Llama 2 Community License: https://github.com/facebookresearch/llama/blob/main/LICENSE
+- **Finetuned from model:** Llama V2 70B
+
+### Usage
+
+To use this model at longer lengths the model needs to be patched to interpolate the longer context
+lengths. It will not work if it is simply loaded with the `AutoModel` framework of `transformers`.
+For full details and usage see:
+
+https://github.com/abacusai/Long-Context
+
+The evaluation section has detailed code for how to load and patch the model for inference (or further fine-tuning).
+Note in particular the `max_position_embeddings` is not relevant since the patched module dynamically reallocates
+the position buffers as required.
+
+The tokenizer corresponding to this model is https://huggingface.co/abacusai/Giraffe-v1-Tokenizer.
+
+Using the code in the repository you can load this model with the following code:
+```python
+from models import load_model, load_tokenizer
+tokenizer = load_tokenizer()
+model = load_model('abacusai/Giraffe-v2-70b-32k', scale=8)
+```