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Browse files- README.md +108 -0
- cal_data.safetensors +3 -0
- config.json +30 -0
- hidden_states.safetensors +3 -0
- job_new.json +0 -0
- measurement.json +0 -0
- mergekit_moe_config.yml +60 -0
- model.safetensors.index.json +1 -0
- output-00001-of-00002.safetensors +3 -0
- output-00002-of-00002.safetensors +3 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +43 -0
README.md
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---
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license: apache-2.0
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tags:
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- moe
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- frankenmoe
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- merge
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- mergekit
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- lazymergekit
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- yam-peleg/Experiment26-7B
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- mlabonne/AlphaMonarch-7B
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base_model:
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- yam-peleg/Experiment26-7B
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- mlabonne/AlphaMonarch-7B
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---
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# MixtureofMerges-MoE-2x7b-v6
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MixtureofMerges-MoE-2x7b-v6 is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [yam-peleg/Experiment26-7B](https://huggingface.co/yam-peleg/Experiment26-7B)
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* [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B)
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## 🧩 Configuration
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```yaml
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base_model: yam-peleg/Experiment26-7B
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gate_mode: hidden
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dtype: bfloat16
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experts:
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- source_model: yam-peleg/Experiment26-7B
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positive_prompts:
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- "Answer this question from the ARC (Argument Reasoning Comprehension)."
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- "Use common sense and logical reasoning skills."
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- "What assumptions does this argument rely on?"
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- "Are these assumptions valid? Explain."
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- "Could this be explained in a different way? Provide an alternative explanation."
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- "Identify any weaknesses in this argument."
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- "Does this argument contain any logical fallacies? If so, which ones?"
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- "Generate a few possible continuations to this scenario."
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- "Demonstrate understanding of everyday commonsense in your response."
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- "Use contextual clues to determine the most likely outcome."
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- "Continue this scenario, but make the writing style sound archaic and overly formal."
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- "This narrative is predictable. Can you introduce an unexpected yet plausible twist?"
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- "The character is angry. Continue this scenario showcasing a furious outburst."
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negative_prompts:
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- "misses key evidence"
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- "overly general"
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- "focuses on irrelevant details"
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- "assumes information not provided"
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- "relies on stereotypes"
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- "repetitive phrases"
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- "overuse of the same words"
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- "contradicts earlier statements - breaks the internal logic of the scenario"
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- "out of character dialogue"
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- "awkward phrasing - sounds unnatural"
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- "doesn't match the given genre"
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- source_model: mlabonne/AlphaMonarch-7B
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positive_prompts:
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- "Answer this question, demonstrating commonsense understanding and using any relevant general knowledge you may have."
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- "Provide a concise summary of this passage, then explain why the highlighted section is essential to the main idea."
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- "Read these two brief articles presenting different viewpoints on the same topic. List their key arguments and highlight where they disagree."
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- "Paraphrase this statement, changing the emotional tone but keeping the core meaning intact. Example: Rephrase a worried statement in a humorous way"
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- "Create a short analogy that helps illustrate the main concept of this article."
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- "Calculate the answer to this math problem"
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- "My mathematical capabilities are strong, allowing me to handle complex mathematical queries"
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- "solve for"
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- "A store sells apples at $0.50 each. If Emily buys 12 apples, how much does she need to pay?"
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- "Isolate x in the following equation: 2x + 5 = 17"
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- "Solve this equation and show your working."
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- "Explain why you used this formula to solve the problem."
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- "Attempt to divide this number by zero. Explain why this cannot be done."
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negative_prompts:
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- "sounds too basic"
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- "understated"
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- "dismisses important details"
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- "avoids the question's nuance"
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- "takes this statement too literally"
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- "incorrect"
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- "inaccurate"
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- "assumed without proof"
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- "rushed calculation"
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- "confuses mathematical concepts"
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- "draws illogical conclusions"
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- "circular reasoning"
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```
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## 💻 Usage
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```python
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!pip install -qU transformers bitsandbytes accelerate
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from transformers import AutoTokenizer
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import transformers
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import torch
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model = "jsfs11/MixtureofMerges-MoE-2x7b-v6"
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tokenizer = AutoTokenizer.from_pretrained(model)
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pipeline = transformers.pipeline(
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"text-generation",
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model=model,
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model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
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)
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messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
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prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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```
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cal_data.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:08be1103ff8fcef33b570f3c0f5ae4cc7f9dc5c3f264105baa55fc9b132ed1be
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size 1638488
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config.json
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{
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"_name_or_path": "yam-peleg/Experiment26-7B",
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"architectures": [
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"MixtralForCausalLM"
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],
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"attention_dropout": 0.0,
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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": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mixtral",
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"num_attention_heads": 32,
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"num_experts_per_tok": 2,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"num_local_experts": 2,
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"output_router_logits": false,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"router_aux_loss_coef": 0.001,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.38.2",
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"use_cache": true,
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"vocab_size": 32000
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}
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hidden_states.safetensors
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:bd0e1d21c3b5f7b72885af2d33264e2f72709fc7b6b512849f179d30f921991f
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size 1677730376
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job_new.json
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See raw diff
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measurement.json
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See raw diff
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mergekit_moe_config.yml
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base_model: yam-peleg/Experiment26-7B
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3 |
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gate_mode: hidden
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4 |
+
dtype: bfloat16
|
5 |
+
experts:
|
6 |
+
- source_model: yam-peleg/Experiment26-7B
|
7 |
+
positive_prompts:
|
8 |
+
- "Answer this question from the ARC (Argument Reasoning Comprehension)."
|
9 |
+
- "Use common sense and logical reasoning skills."
|
10 |
+
- "What assumptions does this argument rely on?"
|
11 |
+
- "Are these assumptions valid? Explain."
|
12 |
+
- "Could this be explained in a different way? Provide an alternative explanation."
|
13 |
+
- "Identify any weaknesses in this argument."
|
14 |
+
- "Does this argument contain any logical fallacies? If so, which ones?"
|
15 |
+
- "Generate a few possible continuations to this scenario."
|
16 |
+
- "Demonstrate understanding of everyday commonsense in your response."
|
17 |
+
- "Use contextual clues to determine the most likely outcome."
|
18 |
+
- "Continue this scenario, but make the writing style sound archaic and overly formal."
|
19 |
+
- "This narrative is predictable. Can you introduce an unexpected yet plausible twist?"
|
20 |
+
- "The character is angry. Continue this scenario showcasing a furious outburst."
|
21 |
+
negative_prompts:
|
22 |
+
- "misses key evidence"
|
23 |
+
- "overly general"
|
24 |
+
- "focuses on irrelevant details"
|
25 |
+
- "assumes information not provided"
|
26 |
+
- "relies on stereotypes"
|
27 |
+
- "repetitive phrases"
|
28 |
+
- "overuse of the same words"
|
29 |
+
- "contradicts earlier statements - breaks the internal logic of the scenario"
|
30 |
+
- "out of character dialogue"
|
31 |
+
- "awkward phrasing - sounds unnatural"
|
32 |
+
- "doesn't match the given genre"
|
33 |
+
- source_model: mlabonne/AlphaMonarch-7B
|
34 |
+
positive_prompts:
|
35 |
+
- "Answer this question, demonstrating commonsense understanding and using any relevant general knowledge you may have."
|
36 |
+
- "Provide a concise summary of this passage, then explain why the highlighted section is essential to the main idea."
|
37 |
+
- "Read these two brief articles presenting different viewpoints on the same topic. List their key arguments and highlight where they disagree."
|
38 |
+
- "Paraphrase this statement, changing the emotional tone but keeping the core meaning intact. Example: Rephrase a worried statement in a humorous way"
|
39 |
+
- "Create a short analogy that helps illustrate the main concept of this article."
|
40 |
+
- "Calculate the answer to this math problem"
|
41 |
+
- "My mathematical capabilities are strong, allowing me to handle complex mathematical queries"
|
42 |
+
- "solve for"
|
43 |
+
- "A store sells apples at $0.50 each. If Emily buys 12 apples, how much does she need to pay?"
|
44 |
+
- "Isolate x in the following equation: 2x + 5 = 17"
|
45 |
+
- "Solve this equation and show your working."
|
46 |
+
- "Explain why you used this formula to solve the problem."
|
47 |
+
- "Attempt to divide this number by zero. Explain why this cannot be done."
|
48 |
+
negative_prompts:
|
49 |
+
- "sounds too basic"
|
50 |
+
- "understated"
|
51 |
+
- "dismisses important details"
|
52 |
+
- "avoids the question's nuance"
|
53 |
+
- "takes this statement too literally"
|
54 |
+
- "incorrect"
|
55 |
+
- "inaccurate"
|
56 |
+
- "assumed without proof"
|
57 |
+
- "rushed calculation"
|
58 |
+
- "confuses mathematical concepts"
|
59 |
+
- "draws illogical conclusions"
|
60 |
+
- "circular reasoning"
|
model.safetensors.index.json
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{"metadata": {"mergekit_version": "0.0.4"}, "weight_map": {"model.embed_tokens.weight": "model-00001-of-00003.safetensors", "model.norm.weight": "model-00001-of-00003.safetensors", "lm_head.weight": "model-00001-of-00003.safetensors", "model.layers.0.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.1.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.2.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.3.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.4.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.5.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.6.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.7.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.8.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.9.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.10.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.11.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.12.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.13.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.14.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.15.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.16.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.17.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.18.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.19.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.20.input_layernorm.weight": "model-00001-of-00003.safetensors", "model.layers.21.input_layernorm.weight": "model-00001-of-00003.safetensors", 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|
18 |
+
"content": "<unk>",
|
19 |
+
"lstrip": false,
|
20 |
+
"normalized": false,
|
21 |
+
"rstrip": false,
|
22 |
+
"single_word": false
|
23 |
+
}
|
24 |
+
}
|
tokenizer.json
ADDED
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tokenizer.model
ADDED
@@ -0,0 +1,3 @@
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|
|
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|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
|
3 |
+
size 493443
|
tokenizer_config.json
ADDED
@@ -0,0 +1,43 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"add_bos_token": true,
|
3 |
+
"add_eos_token": false,
|
4 |
+
"added_tokens_decoder": {
|
5 |
+
"0": {
|
6 |
+
"content": "<unk>",
|
7 |
+
"lstrip": false,
|
8 |
+
"normalized": false,
|
9 |
+
"rstrip": false,
|
10 |
+
"single_word": false,
|
11 |
+
"special": true
|
12 |
+
},
|
13 |
+
"1": {
|
14 |
+
"content": "<s>",
|
15 |
+
"lstrip": false,
|
16 |
+
"normalized": false,
|
17 |
+
"rstrip": false,
|
18 |
+
"single_word": false,
|
19 |
+
"special": true
|
20 |
+
},
|
21 |
+
"2": {
|
22 |
+
"content": "</s>",
|
23 |
+
"lstrip": false,
|
24 |
+
"normalized": false,
|
25 |
+
"rstrip": false,
|
26 |
+
"single_word": false,
|
27 |
+
"special": true
|
28 |
+
}
|
29 |
+
},
|
30 |
+
"additional_special_tokens": [],
|
31 |
+
"bos_token": "<s>",
|
32 |
+
"clean_up_tokenization_spaces": false,
|
33 |
+
"eos_token": "</s>",
|
34 |
+
"legacy": true,
|
35 |
+
"model_max_length": 32768,
|
36 |
+
"pad_token": "<s>",
|
37 |
+
"padding_side": "left",
|
38 |
+
"sp_model_kwargs": {},
|
39 |
+
"spaces_between_special_tokens": false,
|
40 |
+
"tokenizer_class": "LlamaTokenizer",
|
41 |
+
"unk_token": "<unk>",
|
42 |
+
"use_default_system_prompt": false
|
43 |
+
}
|