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Model: LeoLM/leo-mistral-hessianai-7b Source: Original Platform
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README.md
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---
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datasets:
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- oscar-corpus/OSCAR-2301
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- wikipedia
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- bjoernp/tagesschau-2018-2023
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language:
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- en
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- de
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library_name: transformers
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pipeline_tag: text-generation
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license: apache-2.0
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---
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# LAION LeoLM: **L**inguistically **E**nhanced **O**pen **L**anguage **M**odel
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Meet LeoLM-Mistral, the first open and commercially available German Foundation Language Model built on Mistral 7b.
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Our models extend Llama-2's capabilities into German through continued pretraining on a large corpus of German-language and mostly locality specific text.
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Thanks to a compute grant at HessianAI's new supercomputer **42**, we release three foundation models trained with 8k context length.
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[`LeoLM/leo-mistral-hessianai-7b`](https://huggingface.co/LeoLM/leo-mistral-hessianai-7b) under Apache 2.0 and
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[`LeoLM/leo-hessianai-7b`](https://huggingface.co/LeoLM/leo-hessianai-7b) and [`LeoLM/leo-hessianai-13b`](https://huggingface.co/LeoLM/leo-hessianai-13b) under the [Llama-2 community license](https://huggingface.co/meta-llama/Llama-2-70b/raw/main/LICENSE.txt) (70b also coming soon! 👀).
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With this release, we hope to bring a new wave of opportunities to German open-source and commercial LLM research and accelerate adoption.
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Read our [blog post](https://laion.ai/blog/leo-lm/) or our paper (preprint coming soon) for more details!
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*A project by Björn Plüster and Christoph Schuhmann in collaboration with LAION and HessianAI.*
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## Model Details
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- **Finetuned from:** [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
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- **Model type:** Causal decoder-only transformer language model
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- **Language:** English and German
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- **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html)
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- **Contact:** [LAION Discord](https://discord.com/invite/eq3cAMZtCC) or [Björn Plüster](mailto:bjoern.pl@outlook.de)
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## Use in 🤗Transformers
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First install direct dependencies:
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```
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pip install transformers torch accelerate
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```
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If you want faster inference using flash-attention2, you need to install these dependencies:
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```bash
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pip install packaging ninja
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pip install flash-attn
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```
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Then load the model in transformers:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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model = AutoModelForCausalLM.from_pretrained(
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model="LeoLM/leo-mistral-hessianai-7b",
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device_map="auto",
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torch_dtype=torch.bfloat16,
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use_flash_attn_2=True # optional
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)
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```
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## Training parameters
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Note that for Mistral training, we changed learning rate to `1e-5` going down to `1e-6`. We also used Zero stage 3 and bfloat16 dtype.
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## Benchmarks
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config.json
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{
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"_name_or_path": "mistralai/Mistral-7B-v0.1",
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"architectures": [
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"MistralForCausalLM"
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],
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.34.0",
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"use_cache": true,
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"vocab_size": 32000
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}
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}
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||||
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|
||||
10
special_tokens_map.json
Normal file
10
special_tokens_map.json
Normal file
@@ -0,0 +1,10 @@
|
||||
{
|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
"unk_token": "<unk>"
|
||||
}
|
||||
91122
tokenizer.json
Normal file
91122
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
44
tokenizer_config.json
Normal file
44
tokenizer_config.json
Normal file
@@ -0,0 +1,44 @@
|
||||
{
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<unk>",
|
||||
"<s>",
|
||||
"</s>"
|
||||
],
|
||||
"bos_token": "<s>",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"legacy": true,
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": null,
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": true
|
||||
}
|
||||
Reference in New Issue
Block a user