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RichardErkhov/
Rijgersberg_-_GEITje-7B-chat-v2-gguf

Name: Rijgersberg_-_GEITje-7B-chat-v2-gguf
Availability: InStock

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GEITje-7B-chat-v2 - GGUF

Model creator: https://huggingface.co/Rijgersberg/
Original model: https://huggingface.co/Rijgersberg/GEITje-7B-chat-v2/

Name	Quant method	Size
GEITje-7B-chat-v2.Q2_K.gguf	Q2_K	2.53GB
GEITje-7B-chat-v2.IQ3_XS.gguf	IQ3_XS	2.81GB
GEITje-7B-chat-v2.IQ3_S.gguf	IQ3_S	2.96GB
GEITje-7B-chat-v2.Q3_K_S.gguf	Q3_K_S	2.95GB
GEITje-7B-chat-v2.IQ3_M.gguf	IQ3_M	3.06GB
GEITje-7B-chat-v2.Q3_K.gguf	Q3_K	3.28GB
GEITje-7B-chat-v2.Q3_K_M.gguf	Q3_K_M	3.28GB
GEITje-7B-chat-v2.Q3_K_L.gguf	Q3_K_L	3.56GB
GEITje-7B-chat-v2.IQ4_XS.gguf	IQ4_XS	3.67GB
GEITje-7B-chat-v2.Q4_0.gguf	Q4_0	3.83GB
GEITje-7B-chat-v2.IQ4_NL.gguf	IQ4_NL	3.87GB
GEITje-7B-chat-v2.Q4_K_S.gguf	Q4_K_S	3.86GB
GEITje-7B-chat-v2.Q4_K.gguf	Q4_K	4.07GB
GEITje-7B-chat-v2.Q4_K_M.gguf	Q4_K_M	4.07GB
GEITje-7B-chat-v2.Q4_1.gguf	Q4_1	4.24GB
GEITje-7B-chat-v2.Q5_0.gguf	Q5_0	4.65GB
GEITje-7B-chat-v2.Q5_K_S.gguf	Q5_K_S	4.65GB
GEITje-7B-chat-v2.Q5_K.gguf	Q5_K	4.78GB
GEITje-7B-chat-v2.Q5_K_M.gguf	Q5_K_M	4.78GB
GEITje-7B-chat-v2.Q5_1.gguf	Q5_1	5.07GB
GEITje-7B-chat-v2.Q6_K.gguf	Q6_K	5.53GB
GEITje-7B-chat-v2.Q8_0.gguf	Q8_0	7.17GB

Original model description:

license: apache-2.0 base_model: Rijgersberg/GEITje-7B tags:

generated_from_trainer
GEITje
conversational model-index:
name: GEITje-7B-chat-v2 results: [] datasets:
Rijgersberg/no_robots_nl
Rijgersberg/ultrachat_10k_nl
BramVanroy/dutch_chat_datasets language:
nl pipeline_tag: text-generation

GEITje-7B-chat-v2

🤖️ Try the chat model in 🤗 Hugging Face Spaces!

GEITje-7B

GEITje is a large open Dutch language model with 7 billion parameters, based on Mistral 7B. It has been further trained on 10 billion tokens of Dutch text. This has improved its Dutch language skills and increased its knowledge of Dutch topics.

Model description

Mistral – Base Model

GEITje is based on Mistral 7B. It's a large open language model with 7 billion parameters, trained by Mistral AI. According to Mistral AI, the 7B model performs better than Llama 2 13B on all (English-language) benchmarks they tested it on. Mistral 7B has been released under the Apache 2.0 open source license.

GEITje – Trained Further on Dutch Texts

GEITje was created by further training Mistral 7B on no less than 10 billion tokens of Dutch text from the Dutch Gigacorpus and the MADLAD-400 web crawling corpus. It is a so-called full-parameter finetune: performed on all parameters. It is not a PEFT or LoRA finetune. Like Mistral, GEITje has a context length of 8,192 tokens.

GEITje-chat – Finetuned for Dialogues

As a demonstration of GEITje's capabilities for chat applications, two initial chat variants of GEITje have also been finetuned: GEITje-chat and GEITje-chat-v2. They can follow instructions, answer questions, and hold dialogues on a variety of topics.

More info

Read more about GEITje-chat in the 📄 README on GitHub.

Checkpoints

An intermediate checkpoint is available in the checkpoints branch.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-06
train_batch_size: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
0.7832	0.05	609	0.8844
0.6904	0.1	1218	0.8698
0.8195	0.15	1827	0.8583
0.7463	0.2	2436	0.8475
0.6739	0.25	3045	0.8395
0.7604	0.3	3654	0.8332
0.8024	0.35	4263	0.8261
0.6881	0.4	4872	0.8203
0.6466	0.45	5481	0.8167
0.7042	0.5	6090	0.8121
0.702	0.55	6699	0.8081
0.7255	0.6	7308	0.8054
0.7558	0.65	7917	0.8036
0.7587	0.7	8526	0.8022
0.9217	0.75	9135	0.8016
0.6938	0.8	9744	0.8011
0.6962	0.85	10353	0.8011
0.664	0.9	10962	0.8011
0.6544	0.95	11571	0.8011
0.6782	1.0	12180	0.8011

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.1.1+cu121
Datasets 2.15.0
Tokenizers 0.15.0

RichardErkhov/Rijgersberg_-_GEITje-7B-chat-v2-gguf