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Model: aari1995/germeo-7b-laser
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README.md

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+---
+language:
+- de
+license: apache-2.0
+tags:
+- hermeo
+- laser
+datasets:
+- LeoLM/OpenSchnabeltier
+pipeline_tag: conversational
+model-index:
+- name: germeo-7b-laser
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 60.75
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aari1995/germeo-7b-laser
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 82.81
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aari1995/germeo-7b-laser
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 60.57
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aari1995/germeo-7b-laser
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 53.83
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aari1995/germeo-7b-laser
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 75.61
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aari1995/germeo-7b-laser
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 43.37
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aari1995/germeo-7b-laser
+      name: Open LLM Leaderboard
+---
+
+(Evaluation WIP)
+
+## Hermes + Leo + German Laser = Germeo
+
+## Germeo-7B-Laser
+A German-English understanding, but German-only speaking model merged from Hermeo-7B.
+
+### Model details
+
+**Merged from**: leo-mistral-hessianai-7b-chat and DPOpenHermes-7B-v2
+
+**Model type**: Causal decoder-only transformer language model
+
+**Languages**: German replies with English Understanding Capabilities
+
+**Laser-Data**: LeoLM/OpenSchnabeltier
+
+
+This is an early experiment on laser and its influence on language understanding. It generally improves the language understanding capabilities.
+The hypothesis is that it degrades the probability of English replies and increasing those of German replies. The models internal German capabilities are boosted. 
+
+Will keep you updated..
+
+### Acknowledgements:
+
+I would like to thank everyone that participated in making this model and its training possible:
+To [@malteos](https://huggingface.co/malteos) for hermeo
+To [@cognitivecomputations](https://huggingface.co/cognitivecomputations) and Fernando Fernandes Neto for their implementation of LASER
+To [@LeoLM](https://huggingface.co/LeoLM) and Björn for the OpenSchnabeltier dataset.
+
+
+### Prompt format:
+
+```python
+streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
+# Convert prompt to tokens
+prompt_template = """<|im_start|>system
+Du bist ein hilfreicher Assistent.<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant"""
+
+prompt = "Schreibe eine Stellenanzeige für Data Scientist bei AXA!"
+
+final_prompt = prompt_template.format(prompt=prompt)
+```
+
+#### Limit the model to output reply-only:
+  To solve this, you need to implement a custom stopping criteria:
+
+```python
+from transformers import StoppingCriteria
+class GermeoStoppingCriteria(StoppingCriteria):
+  def __init__(self, target_sequence, prompt):
+      self.target_sequence = target_sequence
+      self.prompt=prompt
+
+  def __call__(self, input_ids, scores, **kwargs):
+      # Get the generated text as a string
+      generated_text = tokenizer.decode(input_ids[0])
+      generated_text = generated_text.replace(self.prompt,'')
+      # Check if the target sequence appears in the generated text
+      if self.target_sequence in generated_text:
+          return True  # Stop generation
+
+      return False  # Continue generation
+
+  def __len__(self):
+      return 1
+
+  def __iter__(self):
+      yield self
+```
+This then expects your input prompt (formatted as given into the model), and a stopping criteria, in this case the im_end token. Simply add it to the generation:
+
+```python
+generation_output = model.generate(
+    tokens, 
+    streamer=streamer,
+    max_new_tokens=1012,
+    stopping_criteria=GermeoStoppingCriteria("<|im_end|>", prompt_template.format(prompt=prompt))
+)
+```
+
+### German benchmarks
+
+| **German tasks:**             | **MMLU-DE**    | **Hellaswag-DE** | **ARC-DE**      |**Average**      |
+|-------------------------------|-------------|---------------|--------------|--------------|
+| **Models / Few-shots:**       | _(5 shots)_ | _(10 shots)_  | _(24 shots)_ | |
+| _7B parameters_      |  | |  | |
+| llama-2-7b                    | 0.400       | 0.513         | 0.381        | 0.431  |
+| leo-hessianai-7b              | 0.400       | 0.609         | 0.429        | 0.479 |
+| bloom-6b4-clp-german          | 0.274       | 0.550         | 0.351        | 0.392 |
+| mistral-7b                    | **0.524**       | 0.588         | 0.473        | 0.528 |
+| leo-mistral-hessianai-7b      | 0.481       | 0.663         | 0.485        | 0.543 |
+| leo-mistral-hessianai-7b-chat | 0.458       | 0.617         | 0.465        | 0.513 |
+| DPOpenHermes-7B-v2            | 0.517         | 0.603         | 0.515        | 0.545 |
+| hermeo-7b                     | 0.511       | **0.668**         | **0.528**        | **0.569** |
+| **germeo-7b-laser (this model)**| ?       | ?        | ?      | ? |
+| _13B parameters_      |  | |  | |
+| llama-2-13b                    | 0.469       | 0.581        | 0.468        | 0.506 |
+| leo-hessianai-13b              | **0.486**       | **0.658**         | **0.509**       | **0.551** |
+| _70B parameters_      |  | |  | |
+| llama-2-70b                    | 0.597       | 0.674       | 0.561       | 0.611 |
+| leo-hessianai-70b              | **0.653**       | **0.721**         | **0.600**       | **0.658** |
+
+
+Even though the model does not generate English text without being explicitly asked, performance on English Benchmarks is still up:
+
+### English benchmarks
+
+| **English tasks:**                 | **MMLU**    | **Hellaswag** | **ARC**      | **Average** |
+|------------------------------------|-------------|---------------|--------------|-------------|
+| **Models / Few-shots:**            | _(5 shots)_ | _(10 shots)_  | _(24 shots)_ |             |
+| llama-2-7b                         |       0.466 |         0.786 |        0.530 |       0.594 |
+| leolm-hessianai-7b                 |       0.423 |         0.759 |        0.522 |       0.568 |
+| bloom-6b4-clp-german               |       0.264 |         0.525 |        0.328 |       0.372 |
+| mistral-7b                         |   **0.635** |     **0.832** |        0.607 |   **0.691** |
+| leolm-mistral-hessianai-7b         |       0.550 |         0.777 |        0.518 |       0.615 |
+| hermeo-7b                          |       0.601 |         0.821 |    **0.620** |       0.681 |
+| germeo-7b-laser (this model)       |       0.601 |         0.828 |        0.608 |       0.679 |
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_aari1995__germeo-7b-laser)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |62.82|
+|AI2 Reasoning Challenge (25-Shot)|60.75|
+|HellaSwag (10-Shot)              |82.81|
+|MMLU (5-Shot)                    |60.57|
+|TruthfulQA (0-shot)              |53.83|
+|Winogrande (5-shot)              |75.61|
+|GSM8k (5-shot)                   |43.37|
+

config.json

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+{
+  "_name_or_path": "malteos/hermeo-7b",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.36.2",
+  "use_cache": true,
+  "vocab_size": 32002
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.36.2"
+}

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special_tokens_map.json

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tokenizer_config.json

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