初始化项目，由ModelHub XC社区提供模型
Model: Mabeck/Heidrun-Mistral-7B-chat Source: Original Platform
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Heidrun-Mistral-7B-chat-Q6_K.gguf
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README.md
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README.md
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---
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language:
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- en
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- da
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- mistral
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- trl
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base_model: Mabeck/Heidrun-Mistral-7B-base
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datasets:
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- Mabeck/danish-OpenHermes
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- kobprof/skolegpt-instruct
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license: mit
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pipeline_tag: text-generation
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---
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<img src="https://huggingface.co/Mabeck/Heidrun-Mistral-7B-chat/resolve/main/heidrun.jpeg" alt="Heidrun Logo" width="400">
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# Model description
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Heidrun-Mistral-7B-chat is a chat-model based on [Heidrun-Mistral-7B-base](https://huggingface.co/Mabeck/Heidrun-Mistral-7B-base), finetuned on [danish-OpenHermes](https://huggingface.co/datasets/Mabeck/danish-OpenHermes) and [skoleGPT](https://huggingface.co/datasets/kobprof/skolegpt-instruct) for a instruction/chat format.
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It is a new SOTA Danish open-source LLM and shows very strong performance in logic and reasoning tasks.
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Heidrun-7B ranks 1st among Danish open-sourced LLMs based on the [ScandEval](https://scandeval.com/mainland-scandinavian-nlg/) benchmark and shares 1st place on all Scandinavian languages.
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# Benchmarks
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The following benchmarks have been tested using [ScandEval](https://github.com/ScandEval/ScandEval). Rankings don't include merged models and GPT4 and GPT3.5 ranks 1 and 2:
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- **MMLU-da**: 35.66%+-0.85%/51.68+-0.63%, ranks 3rd
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- **DANSK**: 50.80% ± 2.33% / 34.04% ± 1.76%, ranks 3rd=
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- **Hellaswag-da**: 29.18% ± 0.99%/ 46.64% ± 0.76%, ranks 4th
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# Datasets
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This model is trained on Danish instruction datasets [danish-OpenHermes](Mabeck/danish-OpenHermes) and [skoleGPT](https://huggingface.co/datasets/kobprof/skolegpt-instruct), which have not been safeguarded or alligned.
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Most of the data has been machine-translated and may contain incorrect responses.
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# Samples
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This model uses the ChatML format. Using other formats may degrade the model's performance.
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Samples from the model using ChatML format:
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```
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"<s> <im_start>system
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Du er en AI-hjælper. Du får en opgave fra en bruger hvor du kort og præcist skal forklare svaret.
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<im_end>
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<im_start>user
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Hvilke 3 populære retter findes der i dansk madlavning?
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<im_end>
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<im_start>assistant
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1. Smørrebrød: Smørrebrød er en populær dansk ret, der består af brød med forskellige toppings som røget laks, rejer, ost eller andre ingredienser.
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2. Frikadeller: Frikadeller er en traditionel dansk ret lavet af kødboller af kalvekød, svinekød eller lam, krydret med krydderurter og kogt i smør eller olie.
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3. Rød kål: Rød kål er en populær side ret i dansk madlavning.
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<im_end></s>"
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```
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```
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"<s> <im_start>system
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Du er en AI-hjælper. Du får en opgave fra en bruger hvor du kort og præcist skal forklare svaret.
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<im_end>
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<im_start>user
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Hvilke 3 områder skal fokuseres på for at effektivt tackle klimaforandringer?
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<im_end>
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<im_start>assistant
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1. Energiproduktion: Fokus på vedvarende energikilder som sol, vind og vandkraft for at reducere afhængigheden af fossile brændstoffer og minimere drivhusgasemissioner.
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2. Transport: Fremme bæredygtige transportformer som offentlig transport, cykling og elektriske køretøjer for at reducere luftforurening og afhængigheden af fossile brændstoffer.
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3. Skovbevarelse og affaldshåndtering: Fremme skovbevarelse og bæredygtig skovdrift for at fange kuldioxid og reducere drivhusgasemissioner, samt fremme genbrug og reducere affaldsproduktion for at mindske mængden af drivhusgasemissioner fra affald.
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<im_end></s>"
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```
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# Uploaded model
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- **Developed by:** Mabeck
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- **Finetuned from model :** Mabeck/Heidrun-Mistral-7B-base
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This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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config.json
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"MistralForCausalLM"
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],
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"transformers_version": "4.37.2",
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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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||||
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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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||||
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|
||||
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|
||||
}
|
||||
}
|
||||
30
special_tokens_map.json
Normal file
30
special_tokens_map.json
Normal file
@@ -0,0 +1,30 @@
|
||||
{
|
||||
"bos_token": {
|
||||
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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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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"pad_token": {
|
||||
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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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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
}
|
||||
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.
43
tokenizer_config.json
Normal file
43
tokenizer_config.json
Normal file
@@ -0,0 +1,43 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
|
||||
"added_tokens_decoder": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
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|
||||
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|
||||
"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": [],
|
||||
"bos_token": "<s>",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"legacy": true,
|
||||
"model_max_length": 32768,
|
||||
"pad_token": "<unk>",
|
||||
"padding_side": "right",
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user