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README.md ADDED
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+ ---
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+ license: other
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+ license_name: yi-license
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+ license_link: https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE
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+ language:
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+ - en
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+ library_name: transformers
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+ base_model: []
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+ tags:
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+ - mergekit
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+ - merge
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+ - Yi
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+ ---
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+ # Yi 34B 200K DARE Merge v8
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+
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+ A merge of many 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, without any additional finetuning.
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+
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+ ## Prompt template: Orca-Vicuna
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+ ```
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+ SYSTEM: {system_message}
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+ USER: {prompt}
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+ ASSISTANT:
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+ ```
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+ 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/
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+
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+
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+
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+ ## Running
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+ Being a Yi model, run a lower temperature with 0.05 or higher 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 Yi's huge vocabulary. See the explanation here: https://github.com/ggerganov/llama.cpp/pull/3841
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+
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+ 24GB GPUs can efficiently run Yi-34B-200K models at **40K-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.
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+
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+ I recommend exl2 quantizations profiled on data similar to the desired task. It is especially sensitive to the quantization data at low bpw. I've upload my own fiction-oriented quantizations here: https://huggingface.co/collections/brucethemoose/most-recent-merge-65742644ca03b6c514afa204
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+
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+ 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, litellm or unsloth.
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+
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+
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+ ## Testing Notes
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+
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+ See: https://huggingface.co/brucethemoose/Yi-34B-200K-DARE-merge-v5#testing-notes
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+
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+ An intermediate merge model was created to try and extend the context of several 4k models before adding them to the main merge, as seen in the "megamerge" recipe below. I can upload this upon request
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+
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+ 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.
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+
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+
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+
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+ ## Merge Details
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+ ### Merge Method
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+
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+ 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.
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+
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+ ### Models Merged
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+
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+ The following models were included in the merge:
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+ * https://huggingface.co/kyujinpy/PlatYi-34B-200k-Q-FastChat
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+ * https://huggingface.co/jondurbin/bagel-34b-v0.2
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+ * https://huggingface.co/migtissera/Tess-M-Creative-v1.0
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+ * https://huggingface.co/brucethemoose/SUS-Bagel-200K-DARE-Test
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+ * https://huggingface.co/Mihaiii/Pallas-0.5
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+ * https://huggingface.co/bhenrym14/airoboros-3_1-yi-34b-200k
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+ * https://huggingface.co/adamo1139/Yi-34B-200K-AEZAKMI-v2
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+ * https://huggingface.co/migtissera/Tess-34B-v1.4
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+ * https://huggingface.co/SUSTech/SUS-Chat-34B
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+ * https://huggingface.co/jondurbin/bagel-dpo-34b-v0.2
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+ * https://huggingface.co/bhenrym14/platypus-yi-34b
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+ * https://huggingface.co/Weyaxi/Nous-Hermes-2-SUS-Chat-34B-Slerp
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+ * https://huggingface.co/TriadParty/deepsex-34b
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+ * https://huggingface.co/TriadParty/deepmoney-34b-200k-base
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+ * https://huggingface.co/chargoddard/Yi-34B-200K-Llama
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+ * https://huggingface.co/chargoddard/Yi-34B-Llama
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+
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+ ### Configuration
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+
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+ The following YAML configuration was used to produce this model:
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+
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+ ```yaml
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+ models:
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+ - model: /home/alpha/Models/Raw/chargoddard_Yi-34B-Llama
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+ # No parameters necessary for base model
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+ - model: /home/alpha/Storage/Models/Raw/chargoddard_Yi-34B-200K-Llama
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+ #200K base to extend the context of 4K models, max density as we *want* it to 'interfere'
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+ parameters:
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+ weight: 0.33
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+ density: 1
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+ - model: /home/alpha/Models/Raw/Weyaxi_Nous-Hermes-2-SUS-Chat-34B-Slerp
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+ parameters:
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+ weight: 0.15
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+ density: 0.36
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+ - model: /home/alpha/Models/Raw/jondurbin_bagel-dpo-34b-v0.2
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+ #Mix dpo with sft to tone down dpo
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+ parameters:
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+ weight: 0.06
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+ density: 0.36
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+ - model: /home/alpha/Models/Raw/jondurbin_bagel-34b-v0.2
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+ parameters:
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+ weight: 0.06
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+ density: 0.41
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+ - model: /home/alpha/Models/Raw/bhenrym14_platypus-yi-34b
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+ #Vicuna format
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+ parameters:
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+ weight: 0.19
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+ density: 0.41
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+ # - model: /home/alpha/Models/Raw/01-ai_Yi-34B-Chat #+/home/alpha/Models/Raw/Doctor-Shotgun_limarpv3-yi-llama-34b-lora
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+ # #Can't get lora OR base model to work without erroring out?
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+ # parameters:
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+ # weight: 0.04
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+ # density: 0.36
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+ - model: /home/alpha/Models/Raw/TriadParty_deepsex-34b
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+ #Base model with no prompt
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+ parameters:
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+ weight: 0.21
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+ density: 0.39
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+ merge_method: dare_ties
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+ tokenizer_source: union
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+ base_model: /home/alpha/Models/Raw/chargoddard_Yi-34B-Llama
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+ parameters:
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+ int8_mask: true
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+ dtype: bfloat16
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+ name: 4kmerge-v2
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+ ---
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+ models:
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+ - model: /home/alpha/Storage/Models/Raw/chargoddard_Yi-34B-200K-Llama
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+ # No parameters necessary for base model
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+ - model: /home/alpha/Storage/Models/Raw/migtissera_Tess-34B-v1.4
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+ #Emphasize the beginning of Vicuna format models
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+ parameters:
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+ weight: [0.22, 0.113, 0.113, 0.113, 0.113, 0.113]
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+ density: 0.61
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+ - model: /home/alpha/Models/Raw/Mihaiii_Pallas-0.5
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+ # Vicuna format
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+ parameters:
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+ weight: [0.22, 0.113, 0.113, 0.113, 0.113, 0.113]
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+ density: 0.61
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+ - model: /home/alpha//Storage/Models/Raw/bhenrym14_airoboros-3_1-yi-34b-200k
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+ parameters:
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+ weight: [0.02, 0.081, 0.081, 0.081, 0.081, 0.081]
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+ density: 0.59
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+ - model: /home/alpha/Storage/Models/Raw/jondurbin_bagel-34b-v0.2
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+ #Only the SFT in the main merge since the DPO version seems to have no long context ability at all, and some overfitting(?) issues
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+ parameters:
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+ weight: [0.02, 0.093, 0.093, 0.093, 0.093, 0.093]
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+ density: 0.4
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+ - model: /home/alpha/Storage/Models/Raw/kyujinpy_PlatYi-34B-200k-Q-FastChat
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+ parameters:
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+ weight: [0.02, 0.081, 0.081, 0.081, 0.081, 0.081]
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+ density: 0.59
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+ #- model: /home/alpha/Storage/Models/Raw/ehartford_dolphin-2.2-yi-34b-200k
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+ # Dolphin 200K seems to be funky according to multiple leaderboards and perplexity tests?
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+ # parameters:
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+ # weight: 0.15
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+ # density: 0.6
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+ - model: /home/alpha/Models/Raw/adamo1139_Yi-34B-200K-AEZAKMI-v2
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+ parameters:
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+ weight: [0.02, 0.096, 0.096, 0.096, 0.096, 0.096]
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+ density: 0.59
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+ - model: /home/alpha/Storage/Models/Raw/Nous-Capybara-34B
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+ parameters:
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+ weight: [0.21, 0.115, 0.115, 0.115, 0.115, 0.115]
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+ density: 0.59
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+ - model: 4kmerge-v2
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+ #Previous merge
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+ parameters:
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+ weight: [0.02, 0.115, 0.115, 0.115, 0.115, 0.115]
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+ density: 0.4
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+ - model: /home/alpha/Models/Raw/migtissera_Tess-M-Creative-v1.0
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+ # Vicuna format
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+ parameters:
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+ weight: [0.21, 0.09, 0.09, 0.09, 0.09, 0.09]
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+ density: 0.61
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+ - model: /home/alpha/Models/Raw/TriadParty_deepmoney-34b-200k-base
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+ # No prompt format, native long context full finetune
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+ parameters:
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+ weight: [0.04, 0.103, 0.103, 0.103, 0.103, 0.103]
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+ density: 0.61
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+ merge_method: dare_ties
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+ tokenizer_source: union
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+ base_model: /home/alpha/Storage/Models/Raw/chargoddard_Yi-34B-200K-Llama
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+ parameters:
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+ int8_mask: true
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+ dtype: bfloat16
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+ ```
config.json ADDED
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+ {
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+ "_name_or_path": "/home/alpha/Storage/Models/Raw/chargoddard_Yi-34B-200K-Llama",
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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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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 7168,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 20480,
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+ "max_position_embeddings": 200000,
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+ "model_type": "llama",
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+ "num_attention_heads": 56,
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+ "num_hidden_layers": 60,
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+ "num_key_value_heads": 8,
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+ "pad_token_id": 0,
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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": 5000000.0,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.35.2",
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+ "use_cache": true,
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+ "vocab_size": 64002
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+ }
mergekit_config.yml ADDED
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+ base_model: /home/alpha/Storage/Models/Raw/chargoddard_Yi-34B-200K-Llama
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+ dtype: bfloat16
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+ merge_method: dare_ties
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+ parameters:
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+ int8_mask: 1.0
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+ slices:
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+ - sources:
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+ - layer_range: [0, 60]
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+ model: /home/alpha/Storage/Models/Raw/chargoddard_Yi-34B-200K-Llama
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+ - layer_range: [0, 60]
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+ model: /home/alpha/Storage/Models/Raw/migtissera_Tess-34B-v1.4
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+ parameters:
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+ density: 0.61
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+ weight: [0.22, 0.113, 0.113, 0.113, 0.113, 0.113]
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+ - layer_range: [0, 60]
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+ model: /home/alpha/Models/Raw/Mihaiii_Pallas-0.5
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+ parameters:
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+ density: 0.61
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+ weight: [0.22, 0.113, 0.113, 0.113, 0.113, 0.113]
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+ - layer_range: [0, 60]
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+ model: /home/alpha//Storage/Models/Raw/bhenrym14_airoboros-3_1-yi-34b-200k
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+ parameters:
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+ density: 0.59
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+ weight: [0.02, 0.081, 0.081, 0.081, 0.081, 0.081]
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+ - layer_range: [0, 60]
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+ model: /home/alpha/Storage/Models/Raw/jondurbin_bagel-34b-v0.2
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+ parameters:
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+ density: 0.4
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+ weight: [0.02, 0.093, 0.093, 0.093, 0.093, 0.093]
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+ - layer_range: [0, 60]
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+ model: /home/alpha/Storage/Models/Raw/kyujinpy_PlatYi-34B-200k-Q-FastChat
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+ parameters:
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+ density: 0.59
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+ weight: [0.02, 0.081, 0.081, 0.081, 0.081, 0.081]
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+ - layer_range: [0, 60]
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+ model: /home/alpha/Models/Raw/adamo1139_Yi-34B-200K-AEZAKMI-v2
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+ parameters:
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+ density: 0.59
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+ weight: [0.02, 0.096, 0.096, 0.096, 0.096, 0.096]
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+ - layer_range: [0, 60]
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+ model: /home/alpha/Storage/Models/Raw/Nous-Capybara-34B
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+ parameters:
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+ density: 0.59
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+ weight: [0.21, 0.115, 0.115, 0.115, 0.115, 0.115]
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+ - layer_range: [0, 60]
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+ model: /home/alpha/FastModels/v8/4kmerge-v2
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+ parameters:
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+ density: 0.4
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+ weight: [0.02, 0.115, 0.115, 0.115, 0.115, 0.115]
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+ - layer_range: [0, 60]
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+ model: /home/alpha/Models/Raw/migtissera_Tess-M-Creative-v1.0
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+ parameters:
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+ density: 0.61
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+ weight: [0.21, 0.09, 0.09, 0.09, 0.09, 0.09]
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+ - layer_range: [0, 60]
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+ model: /home/alpha/Models/Raw/TriadParty_deepmoney-34b-200k-base
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+ parameters:
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+ density: 0.61
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+ weight: [0.04, 0.103, 0.103, 0.103, 0.103, 0.103]
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+ tokenizer_source: union
model.safetensors.index.json ADDED
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