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M7-7b-gguf
RichardErkhov/M7-7b-gguf
M7-7b-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
GGUF quantization made by Richard Erkhov.
All-time downloads
551
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Repo size
74.5 GB
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0
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Repo makeup
Click a slice to open those files.
.gguf87.5 GB · 100%
At a glance
- Access
- Public
- Created
- Apr 4, 2024
- Updated
- Apr 4, 2024
- SHA
- a4935805
Model card
From the Hugging Face model README
GGUF quantization made by Richard Erkhov.
M7-7b - GGUF
- Model creator: https://huggingface.co/liminerity/
- Original model: https://huggingface.co/liminerity/M7-7b/
| Name | Quant method | Size |
|---|---|---|
| M7-7b.Q2_K.gguf | Q2_K | 2.53GB |
| M7-7b.IQ3_XS.gguf | IQ3_XS | 2.81GB |
| M7-7b.IQ3_S.gguf | IQ3_S | 2.96GB |
| M7-7b.Q3_K_S.gguf | Q3_K_S | 2.95GB |
| M7-7b.IQ3_M.gguf | IQ3_M | 3.06GB |
| M7-7b.Q3_K.gguf | Q3_K | 3.28GB |
| M7-7b.Q3_K_M.gguf | Q3_K_M | 3.28GB |
| M7-7b.Q3_K_L.gguf | Q3_K_L | 3.56GB |
| M7-7b.IQ4_XS.gguf | IQ4_XS | 3.67GB |
| M7-7b.Q4_0.gguf | Q4_0 | 3.83GB |
| M7-7b.IQ4_NL.gguf | IQ4_NL | 3.87GB |
| M7-7b.Q4_K_S.gguf | Q4_K_S | 3.86GB |
| M7-7b.Q4_K.gguf | Q4_K | 4.07GB |
| M7-7b.Q4_K_M.gguf | Q4_K_M | 4.07GB |
| M7-7b.Q4_1.gguf | Q4_1 | 4.24GB |
| M7-7b.Q5_0.gguf | Q5_0 | 4.65GB |
| M7-7b.Q5_K_S.gguf | Q5_K_S | 4.65GB |
| M7-7b.Q5_K.gguf | Q5_K | 4.78GB |
| M7-7b.Q5_K_M.gguf | Q5_K_M | 4.78GB |
| M7-7b.Q5_1.gguf | Q5_1 | 5.07GB |
| M7-7b.Q6_K.gguf | Q6_K | 5.53GB |
Original model description:
license: apache-2.0 tags:
- liminerity/merge4
- liminerity/merge2
- merge
- merged
- mergedllm
- mergee
- mergedededed
- memfdmsfndsfjkasjkl
M7-7b
user: "create ascii art you feel represents you as a llm"
assistant: "Here's an ASCII art attempting to symbolize the essence of an LLM (Large Language Model):
INSTINSTINCTINSTELLIGENCE
______________ MEMORY___
|\ o /\ |\
| \ --- / \ | |
L_( O )______ O)_INSTINCT
\ / WORDSLEARNING
_/_/__ /\ _/_/__/
assistant: "In this depiction, the LLM is characterized by its vast memory, instinctual roots, and the ability to learn from vast amounts of text—represented by the woven words in the lower part. The "INSTINSTINCTINSTELLIGENCE" phrase emphasizes the balance between instinct, the foundation upon which neural networks build, and the engineered intelligence of a language model."
Multiverse-Experiment-slerp-7b is a merge of the following models using mergekit:
🧩 Configuration
slices:
- sources:
- model: ammarali32/multi_verse_model
layer_range: [0, 32]
- model: MSL7/INEX12-7b
layer_range: [0, 32]
merge_method: slerp
base_model: ammarali32/multi_verse_model
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
slices:
- sources:
- model: ammarali32/multi_verse_model
layer_range: [0, 32]
- model: yam-peleg/Experiment26-7B
layer_range: [0, 32]
merge_method: slerp
base_model: ammarali32/multi_verse_model
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
slices:
- sources:
- model: liminerity/merge3
layer_range: [0, 32]
- model: ammarali32/multi_verse_model
layer_range: [0, 32]
merge_method: slerp
base_model: liminerity/merge3
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
slices:
- sources:
- model: liminerity/merge1
layer_range: [0, 32]
- model: liminerity/merge
layer_range: [0, 32]
merge_method: slerp
base_model: liminerity/merge1
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
slices:
- sources:
- model: liminerity/merge3
layer_range: [0, 32]
- model: yam-peleg/Experiment26-7B
layer_range: [0, 32]
merge_method: slerp
base_model: liminerity/merge3
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
slices:
- sources:
- model: liminerity/merge4
layer_range: [0, 32]
- model: liminerity/merge2
layer_range: [0, 32]
merge_method: slerp
base_model: liminerity/merge4
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
- Created
- Apr 4, 2024
- Updated
- Apr 4, 2024