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Parent(s):
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Upload folder using huggingface_hub
Browse files- README.md +100 -0
- config.json +30 -0
- generation_config.json +6 -0
- huggingface-metadata.txt +43 -0
- model.safetensors.index.json +1002 -0
- output-00001-of-00005.safetensors +3 -0
- output-00002-of-00005.safetensors +3 -0
- output-00003-of-00005.safetensors +3 -0
- output-00004-of-00005.safetensors +3 -0
- output-00005-of-00005.safetensors +3 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer_config.json +43 -0
README.md
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---
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library_name: transformers
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tags:
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- deutsch
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- german
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- seedbox
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- mistral
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- mixtral
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license: apache-2.0
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datasets:
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- seedboxai/multitask_german_examples_32k
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- seedboxai/ultra_feedback_german_modified_v1
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language:
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- de
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pipeline_tag: text-generation
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---
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# KafkaLM-8x7b-German-V0.1
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**KafkaLM 8x7b** is a MoE model based on [Mistral AI´s Mixtral 8x7b](https://mistral.ai/news/mixtral-of-experts/) which was finetuned on an ensemble of popular high-quality open-source instruction sets (translated from English to German).
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KafkaLM 8x7b is a [Seedbox](https://huggingface.co/seedboxai) project trained by [Dennis Dickmann](https://huggingface.co/doubledsbv).
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**Why Kafka?**
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The models are proficient, yet creative, have some tendencies to linguistically push boundaries 😊
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## Model Details
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The purpose of releasing the **KafkaLM series** is to contribute to the German AI community with a set of fine-tuned LLMs that are easy to use in everyday applications across a variety of tasks.
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The main goal was to provide LLMs proficient in German, especially to be used in German-speaking business contexts where English alone is not sufficient.
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### DPO
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The model has been aligned with a german and modified version of the ultra feedback dataset from huggingface.
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### Dataset
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I used a 8k filtered version of the following [seedboxai/multitask_german_examples_32k](https://huggingface.co/datasets/seedboxai/multitask_german_examples_32k)
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### Prompt Format
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This model follows the subsequent prompt format:
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```
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<|system|>
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Du bist ein freundlicher und hilfsbereiter KI-Assistent. Du beantwortest Fragen faktenorientiert und präzise, ohne dabei relevante Fakten auszulassen.</s>
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<|user|>
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Welche Möglichkeiten der energetischen Sanierung habe ich neben Solar und Energiespeicher?</s>
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<|assistant|>
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```
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### Inference
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Getting started with the model is straightforward
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```python
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import transformers
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model_id = "seedboxai/KafkaLM-8x7B-German-V0.1-DPO"
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model = AutoModelForCausalLM.from_pretrained(model_id, load_in_4bit=True, trust_remote_code=True)
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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def generate_prompt(input):
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prompt = ''
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sys_prompt = "Du bist ein freundlicher und hilfsbereiter KI-Assistent. Du beantwortest Fragen faktenorientiert und präzise, ohne dabei relevante Fakten auszulassen."
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prompt += f"<|system|>\n{sys_prompt.strip()}</s>\n"
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prompt += f"<|user|>\n{input.strip()}</s>\n"
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prompt += f"<|assistant|>\n"
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return prompt.strip()
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generate_text = transformers.pipeline(
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model=model, tokenizer=tokenizer,
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return_full_text=True,
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task='text-generation',
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temperature=0.5,
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max_new_tokens=512,
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top_p=0.95,
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top_k=50,
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do_sample=True,
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)
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print(generate_text(generate_prompt("Wer ist eigentlich dieser Kafka?"))
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```
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## Disclaimer
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The license on this model does not constitute legal advice. We are not responsible for the actions of third parties who use this model.
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This model should only be used for research purposes. The original Llama2 license and all restrictions of datasets used to train this model apply.
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config.json
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{
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"_name_or_path": "/workspace/Mixtral-MoE-8x7B/mixtral_FT",
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"architectures": [
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"MixtralForCausalLM"
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],
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"attention_dropout": 0.0,
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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": "mixtral",
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"num_attention_heads": 32,
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"num_experts_per_tok": 2,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"num_local_experts": 8,
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"output_router_logits": false,
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"rms_norm_eps": 1e-05,
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"rope_theta": 1000000.0,
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"router_aux_loss_coef": 0.02,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "float32",
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"transformers_version": "4.38.0.dev0",
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"use_cache": true,
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"vocab_size": 32000
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"transformers_version": "4.38.0.dev0"
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}
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huggingface-metadata.txt
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url: https://huggingface.co/seedboxai/KafkaLM-8x7b-German-V0.1-DPO
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branch: main
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download date: 2024-02-15 10:26:37
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sha256sum:
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model.safetensors.index.json
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