Duplicate from gbueno86/Cathallama-70B
Browse filesCo-authored-by: Guilherme Bueno <[email protected]>
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- README.md +145 -0
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*.7z filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: llama3.1
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language:
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- en
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library_name: transformers
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tags:
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- mergekit
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- merge
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base_model:
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- meta-llama/Meta-Llama-3.1-70B-Instruct
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- turboderp/Cat-Llama-3-70B-instruct
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- Nexusflow/Athene-70B
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---
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+
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/649dc85249ae3a68334adcc6/KxaiZ7rDKkYlix99O9j5H.png)
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**Cathallama**
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=====================================
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Awesome model, my new daily driver.
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Edit: I am seeing a lot of token generations pointing to unknown unicode addresses that didn't show up during testing for this model, so I have stopped using it and I am working on a new version.
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**Notable Performance**
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* 9% overall success rate increase on MMLU-PRO over LLaMA 3.1 70b at Q4_0
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* Strong performance in MMLU-PRO categories overall
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* Great performance during manual testing
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**Creation workflow**
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=====================
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**Models merged**
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* meta-llama/Meta-Llama-3.1-70B-Instruct
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* turboderp/Cat-Llama-3-70B-instruct
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* Nexusflow/Athene-70B
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```
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flowchart TD
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A[Nexusflow_Athene] -->|Merge with| B[Meta-Llama-3.1]
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C[turboderp_Cat] -->|Merge with| D[Meta-Llama-3.1]
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B -->| | E[Merge]
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D -->| | E[Merge]
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E[Merge] -->|Result| F[Cathallama]
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```
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/649dc85249ae3a68334adcc6/bBcB194tAtsZjPUnI1pDQ.png)
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**Testing**
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=====================
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**Hyperparameters**
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---------------
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* **Temperature**: 0.0 for automated, 0.9 for manual
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* **Penalize repeat sequence**: 1.05
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* **Consider N tokens for penalize**: 256
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* **Penalize repetition of newlines**
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* **Top-K sampling**: 40
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* **Top-P sampling**: 0.95
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* **Min-P sampling**: 0.05
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**LLaMAcpp Version**
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------------------
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* b3527-2-g2d5dd7bb
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* -fa -ngl -1 -ctk f16 --no-mmap
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**Tested Files**
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------------------
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* Cathallama-70B.Q4_0.gguf
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* Nexusflow_Athene-70B.Q4_0.gguf
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* turboderp_Cat-Llama-3-70B-instruct.Q4_0.gguf
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* Meta-Llama-3.1-70B-Instruct.Q4_0.gguf
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**Tests**
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--------------
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**Manual testing**
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| Category | Test Case | Cathallama-70B.Q4_0.gguf | Nexusflow_Athene-70B.Q4_0.gguf | turboderp_Cat-Llama-3-70B-instruct.Q4_0.gguf | Meta-Llama-3.1-70B-Instruct.Q4_0.gguf |
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| --- | --- | --- | --- | --- | --- |
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| **Common Sense** | Ball on cup | OK | <span style="color: red;">KO</span> | <span style="color: red;">KO</span> | OK |
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| | Big duck small horse | <span style="color: red;">KO</span> | OK | <span style="color: red;">KO</span> | OK |
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| | Killers | OK | OK | <span style="color: red;">KO</span> | OK |
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| | Strawberry r's | OK | <span style="color: red;">KO</span> | <span style="color: red;">KO</span> | <span style="color: red;">KO</span> |
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| | 9.11 or 9.9 bigger | <span style="color: red;">KO</span> | OK | OK | <span style="color: red;">KO</span> |
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| | Dragon or lens | <span style="color: red;">KO</span> | <span style="color: red;">KO</span> | <span style="color: red;">KO</span> | <span style="color: red;">KO</span> |
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| | Shirts | OK | OK | <span style="color: red;">KO</span> | <span style="color: red;">KO</span> |
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| | Sisters | OK | <span style="color: red;">KO</span> | <span style="color: red;">KO</span> | <span style="color: red;">KO</span> |
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| | Jane faster | OK | OK | OK | OK |
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| **Programming** | JSON | OK | OK | OK | OK |
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| | Python snake game | OK | <span style="color: red;">KO</span> | <span style="color: red;">KO</span> | <span style="color: red;">KO</span> |
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| **Math** | Door window combination | OK | OK | <span style="color: red;">KO</span> | <span style="color: red;">KO</span> |
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| **Smoke** | Poem | OK | OK | OK | OK |
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| | Story | OK | OK | KO | OK |
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*Note: See [sample_generations.txt](https://huggingface.co/gbueno86/Cathallama-70B/blob/main/sample_generations.txt) on the main folder of the repo for the raw generations.*
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**MMLU-PRO**
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| Model | Success % |
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| --- | --- |
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| Cathallama-70B.Q4_0.gguf | **51.0%** |
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| turboderp_Cat-Llama-3-70B-instruct.Q4_0.gguf | 37.0% |
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| Nexusflow_Athene-70B.Q4_0.gguf | 41.0% |
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| Meta-Llama-3.1-70B-Instruct.Q4_0.gguf | 42.0% |
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| MMLU-PRO category| Cathallama-70B.Q4_0.gguf | Nexusflow_Athene-70B.Q4_0.gguf | turboderp_Cat-Llama-3-70B-instruct.Q4_0.gguf | Meta-Llama-3.1-70B-Instruct.Q4_0.gguf |
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| --- | --- | --- | --- | --- |
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| Business | **50.0%** | 45.0% | 20.0% | 40.0% |
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| Law | **40.0%** | 30.0% | 30.0% | 35.0% |
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| Psychology | **85.0%** | 80.0% | 70.0% | 75.0% |
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| Biology | 80.0% | 70.0% | **85.0%** | 80.0% |
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| Chemistry | **55.0%** | 40.0% | 35.0% | 35.0% |
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| History | **65.0%** | 60.0% | 55.0% | **65.0%** |
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| Other | **55.0%** | 50.0% | 45.0% | 50.0% |
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| Health | **75.0%** | 40.0% | 60.0% | 65.0% |
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| Economics | **80.0%** | 75.0% | 65.0% | 70.0% |
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| Math | **45.0%** | 35.0% | 15.0% | 40.0% |
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| Physics | **50.0%** | 45.0% | 45.0% | 45.0% |
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| Computer Science | **60.0%** | 55.0% | 55.0% | **60.0%** |
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| Philosophy | 55.0% | **60.0%** | 45.0% | 50.0% |
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| Engineering | 35.0% | **40.0%** | 25.0% | 35.0% |
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*Note: MMLU-PRO Overall tested with 100 questions. Categories testes with 20 questions from each category.*
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**PubmedQA**
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Model Name | Success% |
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| --- | --- |
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| Cathallama-70B.Q4_0.gguf| 73.00% |
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| turboderp_Cat-Llama-3-70B-instruct.Q4_0.gguf | **76.00%** |
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| Nexusflow_Athene-70B.Q4_0.gguf | 67.00% |
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| Meta-Llama-3.1-70B-Instruct.Q4_0.gguf | 72.00% |
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**Request**
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--------------
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If you are hiring in the EU or can sponsor a visa, PM me :D
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PS. Thank you mradermacher for the GGUFs!
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config.json
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{
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"_name_or_path": "/Volumes/external2/models/Cat-a-Llama-v2",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id": 128001,
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"hidden_act": "silu",
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"hidden_size": 8192,
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"initializer_range": 0.02,
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"intermediate_size": 28672,
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"max_position_embeddings": 8192,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 64,
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"num_hidden_layers": 80,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.43.3",
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"use_cache": true,
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"vocab_size": 128256
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}
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llama.log
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[1723093853] warming up the model with an empty run
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mergekit_config.yml
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base_model: /Volumes/external2/models/Cat-a-Llama-v2
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dtype: bfloat16
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merge_method: slerp
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parameters:
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t:
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- filter: self_attn
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value: [0.0, 0.5, 0.3, 0.7, 1.0]
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- filter: mlp
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value: [1.0, 0.5, 0.7, 0.3, 0.0]
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- value: 0.5
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slices:
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