louisbrulenaudet
commited on
Commit
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Parent(s):
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Initial commit
Browse files- .ipynb_checkpoints/README-checkpoint.md +93 -0
- README.md +92 -0
- config.json +87 -0
- gitattributes.txt +35 -0
- model-00001-of-00004.safetensors +3 -0
- model-00002-of-00004.safetensors +3 -0
- model-00003-of-00004.safetensors +3 -0
- model-00004-of-00004.safetensors +3 -0
- model.safetensors.index.json +0 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer_config.json +44 -0
.ipynb_checkpoints/README-checkpoint.md
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---
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license: other
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license_name: apache-2.0
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language:
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- en
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base_model: louisbrulenaudet/Maxine-34B-stock
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datasets:
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- cognitivecomputations/Dolphin-2.9
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- teknium/OpenHermes-2.5
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- m-a-p/CodeFeedback-Filtered-Instruction
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- cognitivecomputations/dolphin-coder
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- cognitivecomputations/samantha-data
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- microsoft/orca-math-word-problems-200k
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- Locutusque/function-calling-chatml
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- internlm/Agent-FLAN
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library_name: transformers
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tags:
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- mlx
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- merge
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- mergekit
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- louisbrulenaudet/Maxine-34B-stock
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- ConvexAI/Luminex-34B-v0.2
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- fblgit/UNA-34BeagleSimpleMath-32K-v1
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- chemistry
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- biology
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- math
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pipeline_tag: text-generation
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model-index:
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- name: Maxine-34B-stock
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results:
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- task:
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type: text-generation
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metrics:
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- name: Average
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type: Average
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value: 77.28
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- name: ARC
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type: ARC
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value: 74.06
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- name: GSM8K
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type: GSM8K
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value: 72.18
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- name: Winogrande
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type: Winogrande
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value: 83.9
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- name: TruthfulQA
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type: TruthfulQA
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value: 70.18
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- name: HellaSwag
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type: HellaSwag
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value: 86.74
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source:
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name: Open LLM Leaderboard
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
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---
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<center><img src='https://i.imgur.com/dU9dUh0.png' width='500px'></center>
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# mlx-community/Maxine-34B-stock
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This model was converted to MLX format from [`louisbrulenaudet/Maxine-34B-stock`]() using mlx-vlm version **0.15.2**.
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Refer to the [original model card](louisbrulenaudet/Maxine-34B-stock) for more details on the model.
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## Use with mlx
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```bash
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pip install -U mlx-vlm
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python -m mlx_vlm.generate --model mlx-community/Maxine-34B-stock --max-tokens 100 --temp 0.0
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```
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```python
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from mlx_lm import load, generate
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model, tokenizer = load("mlx-community/Maxine-34B-stock")
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response = generate(model, tokenizer, prompt="hello", verbose=True)
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```
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## Citing & Authors
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If you use this code in your research, please use the following BibTeX entry.
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```BibTeX
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@misc{louisbrulenaudet2024,
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author = {Louis Brulé Naudet},
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title = {Maxine-34B-stock, an xtraordinary 34B model},
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year = {2024}
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howpublished = {\url{https://huggingface.co/mlx-community/Maxine-34B-stock}},
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}
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```
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## Feedback
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If you have any feedback, please reach out at [louisbrulenaudet@icloud.com](mailto:louisbrulenaudet@icloud.com).
|
README.md
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@@ -0,0 +1,92 @@
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---
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2 |
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license_name: apache-2.0
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+
language:
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4 |
+
- en
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5 |
+
base_model: louisbrulenaudet/Maxine-34B-stock
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6 |
+
datasets:
|
7 |
+
- cognitivecomputations/Dolphin-2.9
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8 |
+
- teknium/OpenHermes-2.5
|
9 |
+
- m-a-p/CodeFeedback-Filtered-Instruction
|
10 |
+
- cognitivecomputations/dolphin-coder
|
11 |
+
- cognitivecomputations/samantha-data
|
12 |
+
- microsoft/orca-math-word-problems-200k
|
13 |
+
- Locutusque/function-calling-chatml
|
14 |
+
- internlm/Agent-FLAN
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15 |
+
library_name: transformers
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16 |
+
tags:
|
17 |
+
- mlx
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+
- merge
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+
- mergekit
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20 |
+
- louisbrulenaudet/Maxine-34B-stock
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+
- ConvexAI/Luminex-34B-v0.2
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+
- fblgit/UNA-34BeagleSimpleMath-32K-v1
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- chemistry
|
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+
- biology
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+
- math
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pipeline_tag: text-generation
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27 |
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model-index:
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28 |
+
- name: Maxine-34B-stock
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29 |
+
results:
|
30 |
+
- task:
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31 |
+
type: text-generation
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32 |
+
metrics:
|
33 |
+
- name: Average
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34 |
+
type: Average
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35 |
+
value: 77.28
|
36 |
+
- name: ARC
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37 |
+
type: ARC
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38 |
+
value: 74.06
|
39 |
+
- name: GSM8K
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40 |
+
type: GSM8K
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41 |
+
value: 72.18
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42 |
+
- name: Winogrande
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43 |
+
type: Winogrande
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44 |
+
value: 83.9
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45 |
+
- name: TruthfulQA
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46 |
+
type: TruthfulQA
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47 |
+
value: 70.18
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48 |
+
- name: HellaSwag
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49 |
+
type: HellaSwag
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50 |
+
value: 86.74
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51 |
+
source:
|
52 |
+
name: Open LLM Leaderboard
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53 |
+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
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54 |
+
---
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55 |
+
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<center><img src='https://i.imgur.com/dU9dUh0.png' width='500px'></center>
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57 |
+
|
58 |
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# mlx-community/Maxine-34B-stock
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59 |
+
|
60 |
+
This model was converted to MLX format from [`louisbrulenaudet/Maxine-34B-stock`]() using mlx-vlm version **0.15.2**.
|
61 |
+
Refer to the [original model card](louisbrulenaudet/Maxine-34B-stock) for more details on the model.
|
62 |
+
|
63 |
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## Use with mlx
|
64 |
+
|
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```bash
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pip install -U mlx-vlm
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python -m mlx_vlm.generate --model mlx-community/Maxine-34B-stock --max-tokens 100 --temp 0.0
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```
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```python
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from mlx_lm import load, generate
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model, tokenizer = load("mlx-community/Maxine-34B-stock")
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response = generate(model, tokenizer, prompt="hello", verbose=True)
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```
|
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+
|
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## Citing & Authors
|
78 |
+
|
79 |
+
If you use this code in your research, please use the following BibTeX entry.
|
80 |
+
|
81 |
+
```BibTeX
|
82 |
+
@misc{louisbrulenaudet2024,
|
83 |
+
author = {Louis Brulé Naudet},
|
84 |
+
title = {Maxine-34B-stock, an xtraordinary 34B model},
|
85 |
+
year = {2024}
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howpublished = {\url{https://huggingface.co/mlx-community/Maxine-34B-stock}},
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}
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```
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## Feedback
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+
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+
If you have any feedback, please reach out at [louisbrulenaudet@icloud.com](mailto:louisbrulenaudet@icloud.com).
|
config.json
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{
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"vocab_size": 64000,
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"max_position_embeddings": 200000,
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"hidden_size": 7168,
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"intermediate_size": 20480,
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"num_hidden_layers": 60,
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"num_attention_heads": 56,
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"num_key_value_heads": 8,
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"hidden_act": "silu",
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"initializer_range": 0.02,
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"rms_norm_eps": 1e-05,
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"pretraining_tp": 1,
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"use_cache": true,
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"rope_theta": 5000000.0,
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"rope_scaling": null,
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"attention_bias": false,
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"attention_dropout": 0.0,
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"mlp_bias": false,
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"return_dict": true,
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"output_hidden_states": false,
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"output_attentions": false,
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"torchscript": false,
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"torch_dtype": "bfloat16",
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"use_bfloat16": false,
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"tf_legacy_loss": false,
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"pruned_heads": {},
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"tie_word_embeddings": false,
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"chunk_size_feed_forward": 0,
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"is_encoder_decoder": false,
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"is_decoder": false,
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"cross_attention_hidden_size": null,
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"add_cross_attention": false,
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"tie_encoder_decoder": false,
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"max_length": 20,
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"min_length": 0,
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"do_sample": false,
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"early_stopping": false,
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"num_beams": 1,
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"num_beam_groups": 1,
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"diversity_penalty": 0.0,
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"temperature": 1.0,
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"top_k": 50,
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"top_p": 1.0,
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"typical_p": 1.0,
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"repetition_penalty": 1.0,
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"length_penalty": 1.0,
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"no_repeat_ngram_size": 0,
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"encoder_no_repeat_ngram_size": 0,
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"bad_words_ids": null,
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"num_return_sequences": 1,
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"output_scores": false,
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"return_dict_in_generate": false,
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"forced_bos_token_id": null,
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"forced_eos_token_id": null,
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"remove_invalid_values": false,
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"exponential_decay_length_penalty": null,
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"suppress_tokens": null,
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"begin_suppress_tokens": null,
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"architectures": [
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"LlamaForCausalLM"
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],
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"finetuning_task": null,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1"
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},
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1
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},
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"tokenizer_class": null,
|
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"prefix": null,
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"bos_token_id": 1,
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"pad_token_id": 0,
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"eos_token_id": 2,
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"sep_token_id": null,
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"decoder_start_token_id": null,
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"task_specific_params": null,
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"problem_type": null,
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"_name_or_path": "/home/jupyter/.cache/huggingface/hub/models--louisbrulenaudet--Maxine-34B-stock/snapshots/11ab34e48d24d3a1105280433b09edc0665db09a",
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"transformers_version": "4.42.3",
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"model_type": "llama",
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"quantization": {
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"group_size": 64,
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"bits": 4
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}
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}
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gitattributes.txt
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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*.bin filter=lfs diff=lfs merge=lfs -text
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*.bz2 filter=lfs diff=lfs merge=lfs -text
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*.ckpt filter=lfs diff=lfs merge=lfs -text
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*.ftz filter=lfs diff=lfs merge=lfs -text
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*.gz filter=lfs diff=lfs merge=lfs -text
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*.h5 filter=lfs diff=lfs merge=lfs -text
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*.joblib filter=lfs diff=lfs merge=lfs -text
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*.lfs.* filter=lfs diff=lfs merge=lfs -text
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*.mlmodel filter=lfs diff=lfs merge=lfs -text
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*.model filter=lfs diff=lfs merge=lfs -text
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*.msgpack filter=lfs diff=lfs merge=lfs -text
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*.npy filter=lfs diff=lfs merge=lfs -text
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*.npz filter=lfs diff=lfs merge=lfs -text
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*.onnx filter=lfs diff=lfs merge=lfs -text
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