Initial commit of model

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.model.bak filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+language:
+- en
+license: other
+library_name: transformers
+tags:
+- mergekit
+- merge
+- Yi
+license_name: yi-license
+license_link: https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE
+base_model: []
+model-index:
+- name: Yi-34B-200K-DARE-merge-v7
+  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: 68.09
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=brucethemoose/Yi-34B-200K-DARE-merge-v7
+      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: 85.99
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=brucethemoose/Yi-34B-200K-DARE-merge-v7
+      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: 77.3
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=brucethemoose/Yi-34B-200K-DARE-merge-v7
+      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: 58.9
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=brucethemoose/Yi-34B-200K-DARE-merge-v7
+      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: 83.11
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=brucethemoose/Yi-34B-200K-DARE-merge-v7
+      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: 65.35
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=brucethemoose/Yi-34B-200K-DARE-merge-v7
+      name: Open LLM Leaderboard
+---
+# Possibly made obsolete by: https://huggingface.co/brucethemoose/Yi-34B-200K-DARE-megamerge-v8
+
+
+
+# Yi 34B 200K DARE Merge v7
+
+A merge of several Yi 34B 200K models using the new DARE Ties method via mergekit. The goal is to create a merge model that excels at 32K+ context performance. 
+
+## Prompt template: Orca-Vicuna
+```
+SYSTEM: {system_message}
+USER: {prompt}
+ASSISTANT:
+```
+It might recognize ChatML, and possibly Alpaca-like formats. Raw prompting as described here is also effective: https://old.reddit.com/r/LocalLLaMA/comments/18zqy4s/the_secret_to_writing_quality_stories_with_llms/
+
+
+
+## Running
+Being a Yi model, try running a lower temperature with 0.02-0.06 MinP, a little repetition penalty, maybe mirostat with a low tau, and no other samplers. Yi tends to run "hot" by default, and it really needs a low temperature + MinP to cull the huge vocabulary.
+
+24GB GPUs can efficiently run Yi-34B-200K models at **45K-90K context** with exllamav2, and performant UIs like [exui](https://github.com/turboderp/exui). I go into more detail in this [post](https://old.reddit.com/r/LocalLLaMA/comments/1896igc/how_i_run_34b_models_at_75k_context_on_24gb_fast/). 16GB GPUs can still run the high context with aggressive quantization.
+
+To load/train this in full-context backends like transformers, you *must* change `max_position_embeddings` in config.json to a lower value than 200,000, otherwise you will OOM! I do not recommend running high context without context-efficient backends like exllamav2 or unsloth.
+
+
+## Testing Notes
+
+See: https://huggingface.co/brucethemoose/Yi-34B-200K-DARE-merge-v5#testing-notes
+
+A "4k" merge model was created to try and extend the context of SUS Chat and DPO-bagel before adding them to the merge: https://huggingface.co/brucethemoose/SUS-Bagel-200K-DARE-Test
+
+In addition, the weight gradients are biased towards Vicuna-format models in the first few layers to try and "emphasize" the Orca-Vicuna prompt template. How sucessful this is remains to be seen. 
+
+
+### Merge Method
+
+This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using /home/alpha/Storage/Models/Raw/chargoddard_Yi-34B-200K-Llama as a base.
+
+### Models Merged
+
+The following models were included in the merge:
+* https://huggingface.co/kyujinpy/PlatYi-34B-200k-Q-FastChat
+* https://huggingface.co/jondurbin/bagel-34b-v0.2
+* https://huggingface.co/NousResearch/Nous-Capybara-34B
+* https://huggingface.co/migtissera/Tess-M-Creative-v1.0
+* https://huggingface.co/brucethemoose/SUS-Bagel-200K-DARE-Test
+* https://huggingface.co/Mihaiii/Pallas-0.5
+* https://huggingface.co/bhenrym14/airoboros-3_1-yi-34b-200k
+* https://huggingface.co/adamo1139/Yi-34B-200K-AEZAKMI-v2
+* https://huggingface.co/migtissera/Tess-34B-v1.4
+* https://huggingface.co/SUSTech/SUS-Chat-34B
+* https://huggingface.co/jondurbin/bagel-dpo-34b-v0.2
+* https://huggingface.co/chargoddard/Yi-34B-200K-Llama
+* https://huggingface.co/chargoddard/Yi-34B-Llama
+
+
+### Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+models:
+  - model: /home/alpha/Storage/Models/Raw/chargoddard_Yi-34B-200K-Llama
+    # No parameters necessary for base model
+  - model: /home/alpha/Storage/Models/Raw/migtissera_Tess-34B-v1.4
+    parameters:
+      weight: [0.23, 0.125, 0.125, 0.125, 0.125, 0.125]
+      density: 0.59
+  - model: /home/alpha/Models/Raw/Mihaiii_Pallas-0.5
+    parameters:
+      weight: [0.23, 0.125, 0.125, 0.125, 0.125, 0.125]
+      density: 0.59
+  - model: /home/alpha//Storage/Models/Raw/bhenrym14_airoboros-3_1-yi-34b-200k
+    parameters:
+      weight: [0.02, 0.106, 0.106, 0.106, 0.106, 0.106]
+      density: 0.59
+  - model: /home/alpha/Storage/Models/Raw/jondurbin_bagel-34b-v0.2
+    #Only the SFT in the main merge since the DPO version seems to have no long context ability at all
+    parameters:
+      weight: [0.02, 0.100, 0.100, 0.100, 0.100, 0.100]
+      density: 0.4
+  - model: /home/alpha/Storage/Models/Raw/kyujinpy_PlatYi-34B-200k-Q-FastChat
+    parameters:
+      weight: [0.02, 0.100, 0.100, 0.100, 0.100, 0.100]
+      density: 0.59
+  #- model: /home/alpha/Storage/Models/Raw/ehartford_dolphin-2.2-yi-34b-200k
+  #  Dolphin 200K seems to be funky according to multiple leaderboards and perplexity tests?
+  #  parameters:
+  #    weight: 0.15
+  #    density: 0.6
+  - model: /home/alpha/Models/Raw/adamo1139_Yi-34B-200K-AEZAKMI-v2
+    parameters:
+      weight: [0.02, 0.110, 0.110, 0.110, 0.110, 0.110]
+      density: 0.59
+  - model: /home/alpha/Storage/Models/Raw/Nous-Capybara-34B
+    parameters:
+      weight:  [0.22, 0.126, 0.126, 0.126, 0.126, 0.126]
+      density: 0.59
+  - model: /home/alpha/Storage/Models/Raw/4kmerge
+    parameters:
+      weight: [0.02,  0.108, 0.108, 0.108, 0.108, 0.108]
+      density: 0.5
+  - model: /home/alpha/Models/Raw/migtissera_Tess-M-Creative-v1.0
+    parameters:
+      weight: [0.22, 0.100, 0.100, 0.100, 0.100, 0.10]
+      density: 0.59
+merge_method: dare_ties
+tokenizer_source: union
+base_model: /home/alpha/Storage/Models/Raw/chargoddard_Yi-34B-200K-Llama
+parameters:
+  int8_mask: true
+dtype: bfloat16
+
+```
+
+The following config was used for the "4kmerge" model:
+
+```yaml
+models:
+  - model: /home/alpha/Models/Raw/chargoddard_Yi-34B-Llama
+  # No parameters necessary for base model
+  - model: /home/alpha/Storage/Models/Raw/chargoddard_Yi-34B-200K-Llama
+    parameters:
+      weight: 0.5
+      density: 1
+  - model: /home/alpha/Models/Raw/SUSTech_SUS-Chat-34B
+    parameters:
+      weight: 0.2
+      density: 0.12
+  - model: /home/alpha/Models/Raw/jondurbin_bagel-dpo-34b-v0.2
+    parameters:
+      weight: 0.2
+      density: 0.15
+  - model: /home/alpha/Models/Raw/jondurbin_bagel-34b-v0.2
+    parameters:
+      weight: 0.1
+      density: 0.12
+merge_method: dare_ties
+tokenizer_source: union
+base_model: /home/alpha/Models/Raw/chargoddard_Yi-34B-Llama
+parameters:
+  int8_mask: true
+dtype: bfloat16
+```
+
+
+
+# [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_brucethemoose__Yi-34B-200K-DARE-merge-v7)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |73.12|
+|AI2 Reasoning Challenge (25-Shot)|68.09|
+|HellaSwag (10-Shot)              |85.99|
+|MMLU (5-Shot)                    |77.30|
+|TruthfulQA (0-shot)              |58.90|
+|Winogrande (5-shot)              |83.11|
+|GSM8k (5-shot)                   |65.35|
+

config.json

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+{
+    "_name_or_path": "/home/alpha/Storage/Models/Raw/chargoddard_Yi-34B-200K-Llama",
+    "architectures": [
+        "LlamaForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 1,
+    "eos_token_id": 2,
+    "hidden_act": "silu",
+    "hidden_size": 7168,
+    "initializer_range": 0.02,
+    "intermediate_size": 20480,
+    "max_position_embeddings": 200000,
+    "model_type": "llama",
+    "num_attention_heads": 56,
+    "num_hidden_layers": 60,
+    "num_key_value_heads": 8,
+    "pad_token_id": 0,
+    "pretraining_tp": 1,
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": null,
+    "rope_theta": 5000000.0,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.36.2",
+    "use_cache": true,
+    "vocab_size": 64002,
+    "quantization_config": {
+        "quant_method": "exl2",
+        "version": "0.0.15",
+        "bits": 4.0,
+        "head_bits": 6,
+        "calibration": {
+            "rows": 100,
+            "length": 2048,
+            "dataset": "(default)"
+        }
+    }
+}

model.safetensors.index.json

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