File size: 5,039 Bytes
a0d1186
dc947e9
 
a0d1186
dc947e9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a0d1186
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
---
base_model: ibm-granite/granite-3.0-1b-a400m-instruct
license: apache-2.0
pipeline_tag: text-generation
tags:
- language
- granite-3.0
quantized_by: bartowski
inference: false
model-index:
- name: granite-3.0-2b-instruct
  results:
  - task:
      type: text-generation
    dataset:
      name: IFEval
      type: instruction-following
    metrics:
    - type: pass@1
      value: 32.39
      name: pass@1
    - type: pass@1
      value: 6.17
      name: pass@1
  - task:
      type: text-generation
    dataset:
      name: AGI-Eval
      type: human-exams
    metrics:
    - type: pass@1
      value: 20.35
      name: pass@1
    - type: pass@1
      value: 32.0
      name: pass@1
    - type: pass@1
      value: 12.21
      name: pass@1
  - task:
      type: text-generation
    dataset:
      name: OBQA
      type: commonsense
    metrics:
    - type: pass@1
      value: 38.4
      name: pass@1
    - type: pass@1
      value: 47.55
      name: pass@1
    - type: pass@1
      value: 65.59
      name: pass@1
    - type: pass@1
      value: 61.17
      name: pass@1
    - type: pass@1
      value: 49.11
      name: pass@1
  - task:
      type: text-generation
    dataset:
      name: BoolQ
      type: reading-comprehension
    metrics:
    - type: pass@1
      value: 70.12
      name: pass@1
    - type: pass@1
      value: 1.27
      name: pass@1
  - task:
      type: text-generation
    dataset:
      name: ARC-C
      type: reasoning
    metrics:
    - type: pass@1
      value: 41.21
      name: pass@1
    - type: pass@1
      value: 23.07
      name: pass@1
    - type: pass@1
      value: 31.77
      name: pass@1
  - task:
      type: text-generation
    dataset:
      name: HumanEvalSynthesis
      type: code
    metrics:
    - type: pass@1
      value: 30.18
      name: pass@1
    - type: pass@1
      value: 26.22
      name: pass@1
    - type: pass@1
      value: 21.95
      name: pass@1
    - type: pass@1
      value: 15.4
      name: pass@1
  - task:
      type: text-generation
    dataset:
      name: GSM8K
      type: math
    metrics:
    - type: pass@1
      value: 26.31
      name: pass@1
    - type: pass@1
      value: 10.88
      name: pass@1
  - task:
      type: text-generation
    dataset:
      name: PAWS-X (7 langs)
      type: multilingual
    metrics:
    - type: pass@1
      value: 45.84
      name: pass@1
    - type: pass@1
      value: 11.8
      name: pass@1
---
## 💫 Community Model> granite 3.0 1b a400m instruct by Ibm-Granite

*👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)*.

**Model creator:** [ibm-granite](https://huggingface.co/ibm-granite)<br>
**Original model**: [granite-3.0-1b-a400m-instruct](https://huggingface.co/ibm-granite/granite-3.0-1b-a400m-instruct)<br>
**GGUF quantization:** provided by [bartowski](https://huggingface.co/bartowski) based on `llama.cpp` release [b3930](https://github.com/ggerganov/llama.cpp/releases/tag/b3930)<br>

## Technical Details

This is an MoE model with 1b parameters and 400m activated parameters, making it blazing fast for inference.

Tuned on permissive open source datasets and internal synthetic datasets.

This model is designed to respond to general instructions and can be used to build AI assistants for multiple domains.

Supported Languages: English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, and Chinese.

Context length of 4096 tokens.

## Special thanks

🙏 Special thanks to [Georgi Gerganov](https://github.com/ggerganov) and the whole team working on [llama.cpp](https://github.com/ggerganov/llama.cpp/) for making all of this possible.

## Disclaimers

LM Studio is not the creator, originator, or owner of any Model featured in the Community Model Program. Each Community Model is created and provided by third parties. LM Studio does not endorse, support, represent or guarantee the completeness, truthfulness, accuracy, or reliability of any Community Model.  You understand that Community Models can produce content that might be offensive, harmful, inaccurate or otherwise inappropriate, or deceptive. Each Community Model is the sole responsibility of the person or entity who originated such Model. LM Studio may not monitor or control the Community Models and cannot, and does not, take responsibility for any such Model. LM Studio disclaims all warranties or guarantees about the accuracy, reliability or benefits of the Community Models.  LM Studio further disclaims any warranty that the Community Model will meet your requirements, be secure, uninterrupted or available at any time or location, or error-free, viruses-free, or that any errors will be corrected, or otherwise. You will be solely responsible for any damage resulting from your use of or access to the Community Models, your downloading of any Community Model, or use of any other Community Model provided by or through LM Studio.