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Model: budecosystem/genz-13b-infinite
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---
license: llama2
---
## Introducing GenZ Infinite
The model is a finetuned version of Genz-13B-v2 with a context size of 16K. The model architecture is updated to have lamda attention from the LM-Infinite paper which gives the model capability of 120K+ sequence length without affecting the preplexity
## Generate responses
Use the generate.py file from the [github repo](https://github.com/BudEcosystem/genz-infinite)
```
python generate.py --base_model budecosystem/genz-13b-infinite
```
You can integrate the model in your code my loading convert_llama_model function.
```python
import torch
from transformers import GenerationConfig, AutoModelForCausalLM, AutoTokenizer
from model.llama import convert_llama_model
local_branch = 2048
global_branch = 10
limit_distance = 2048
model = AutoModelForCausalLM.from_pretrained(
"budecosystem/genz-13b-infinite",
torch_dtype=torch.float16,
device_map="auto",
)
model = convert_llama_model(model, local_branch, global_branch)
```
## Evaluation
| Task | 4096 | 5120 | 8192 | 16384 |
| :----:|:---------:| :--------:| :--------:| :--------:|
|Passkey retreival | 100 | 75 | 48 | 30 |
## Training details
The model is trained of 4 A100 80GB for approximately 55hrs.
| Hyperparameters | Value |
| :----------------------------| :-----: |
| per_device_train_batch_size | 1 |
| gradient_accumulation_steps | 1 |
| epoch | 3 |
| steps | 8550 |
| learning_rate | 2e-4 |
| lr schedular type | cosine |
| warmup steps | 1000 |
| optimizer | adamw |
| fp16 | True |
| GPU | 4 A100 80GB |
### Acknowledgments
We'd like to thank the open-source community and the researchers whose foundational work laid the path to this model. Special shoutout to the authors of [LM-Infinite paper](https://arxiv.org/abs/2308.16137) and the [GitHub repo](https://github.com/Glaciohound/LM-Infinite)

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{
"_name_or_path": "budecosystem/genz-13b-infinite",
"architectures": [
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"bos_token_id": 1,
"eos_token_id": 2,
"hidden_act": "silu",
"hidden_size": 5120,
"initializer_range": 0.02,
"intermediate_size": 13824,
"max_position_embeddings": 4096,
"model_type": "llama",
"num_attention_heads": 40,
"num_hidden_layers": 40,
"num_key_value_heads": 40,
"pad_token_id": 0,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"tie_word_embeddings": false,
"torch_dtype": "float16",
"transformers_version": "4.29.0.dev0",
"use_cache": true,
"vocab_size": 32000
}

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