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README.md CHANGED
@@ -1,23 +1,16 @@
1
  ---
2
- license: mit
3
- license_link: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct/resolve/main/LICENSE
4
  language:
5
  - en
6
- - fr
7
- pipeline_tag: text-generation
8
  tags:
9
- - nlp
10
- - code
 
 
11
  - TensorBlock
12
  - GGUF
13
- inference:
14
- parameters:
15
- temperature: 0
16
- widget:
17
- - messages:
18
- - role: user
19
- content: Can you provide ways to eat combinations of bananas and dragonfruits?
20
- base_model: microsoft/Phi-3-mini-4k-instruct
21
  ---
22
 
23
  <div style="width: auto; margin-left: auto; margin-right: auto">
@@ -31,9 +24,9 @@ base_model: microsoft/Phi-3-mini-4k-instruct
31
  </div>
32
  </div>
33
 
34
- ## microsoft/Phi-3-mini-4k-instruct - GGUF
35
 
36
- This repo contains GGUF format model files for [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
37
 
38
  The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
39
 
@@ -51,16 +44,16 @@ The files were quantized using machines provided by [TensorBlock](https://tensor
51
 
52
  | Filename | Quant type | File Size | Description |
53
  | -------- | ---------- | --------- | ----------- |
54
- | [Phi-3-mini-4k-instruct-Q2_K.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q2_K.gguf) | Q2_K | 1.319 GB | smallest, significant quality loss - not recommended for most purposes |
55
  | [Phi-3-mini-4k-instruct-Q3_K_S.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q3_K_S.gguf) | Q3_K_S | 1.566 GB | very small, high quality loss |
56
- | [Phi-3-mini-4k-instruct-Q3_K_M.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q3_K_M.gguf) | Q3_K_M | 1.821 GB | very small, high quality loss |
57
- | [Phi-3-mini-4k-instruct-Q3_K_L.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q3_K_L.gguf) | Q3_K_L | 1.944 GB | small, substantial quality loss |
58
  | [Phi-3-mini-4k-instruct-Q4_0.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q4_0.gguf) | Q4_0 | 2.027 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
59
- | [Phi-3-mini-4k-instruct-Q4_K_S.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q4_K_S.gguf) | Q4_K_S | 2.038 GB | small, greater quality loss |
60
- | [Phi-3-mini-4k-instruct-Q4_K_M.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q4_K_M.gguf) | Q4_K_M | 2.229 GB | medium, balanced quality - recommended |
61
  | [Phi-3-mini-4k-instruct-Q5_0.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q5_0.gguf) | Q5_0 | 2.460 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
62
  | [Phi-3-mini-4k-instruct-Q5_K_S.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q5_K_S.gguf) | Q5_K_S | 2.460 GB | large, low quality loss - recommended |
63
- | [Phi-3-mini-4k-instruct-Q5_K_M.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q5_K_M.gguf) | Q5_K_M | 2.622 GB | large, very low quality loss - recommended |
64
  | [Phi-3-mini-4k-instruct-Q6_K.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q6_K.gguf) | Q6_K | 2.920 GB | very large, extremely low quality loss |
65
  | [Phi-3-mini-4k-instruct-Q8_0.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q8_0.gguf) | Q8_0 | 3.782 GB | very large, extremely low quality loss - not recommended |
66
 
 
1
  ---
 
 
2
  language:
3
  - en
4
+ library_name: transformers
5
+ license: mit
6
  tags:
7
+ - unsloth
8
+ - transformers
9
+ - phi3
10
+ - phi
11
  - TensorBlock
12
  - GGUF
13
+ base_model: unsloth/Phi-3-mini-4k-instruct
 
 
 
 
 
 
 
14
  ---
15
 
16
  <div style="width: auto; margin-left: auto; margin-right: auto">
 
24
  </div>
25
  </div>
26
 
27
+ ## unsloth/Phi-3-mini-4k-instruct - GGUF
28
 
29
+ This repo contains GGUF format model files for [unsloth/Phi-3-mini-4k-instruct](https://huggingface.co/unsloth/Phi-3-mini-4k-instruct).
30
 
31
  The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4011](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
32
 
 
44
 
45
  | Filename | Quant type | File Size | Description |
46
  | -------- | ---------- | --------- | ----------- |
47
+ | [Phi-3-mini-4k-instruct-Q2_K.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q2_K.gguf) | Q2_K | 1.348 GB | smallest, significant quality loss - not recommended for most purposes |
48
  | [Phi-3-mini-4k-instruct-Q3_K_S.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q3_K_S.gguf) | Q3_K_S | 1.566 GB | very small, high quality loss |
49
+ | [Phi-3-mini-4k-instruct-Q3_K_M.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q3_K_M.gguf) | Q3_K_M | 1.749 GB | very small, high quality loss |
50
+ | [Phi-3-mini-4k-instruct-Q3_K_L.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q3_K_L.gguf) | Q3_K_L | 1.905 GB | small, substantial quality loss |
51
  | [Phi-3-mini-4k-instruct-Q4_0.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q4_0.gguf) | Q4_0 | 2.027 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
52
+ | [Phi-3-mini-4k-instruct-Q4_K_S.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q4_K_S.gguf) | Q4_K_S | 2.043 GB | small, greater quality loss |
53
+ | [Phi-3-mini-4k-instruct-Q4_K_M.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q4_K_M.gguf) | Q4_K_M | 2.160 GB | medium, balanced quality - recommended |
54
  | [Phi-3-mini-4k-instruct-Q5_0.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q5_0.gguf) | Q5_0 | 2.460 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
55
  | [Phi-3-mini-4k-instruct-Q5_K_S.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q5_K_S.gguf) | Q5_K_S | 2.460 GB | large, low quality loss - recommended |
56
+ | [Phi-3-mini-4k-instruct-Q5_K_M.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q5_K_M.gguf) | Q5_K_M | 2.529 GB | large, very low quality loss - recommended |
57
  | [Phi-3-mini-4k-instruct-Q6_K.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q6_K.gguf) | Q6_K | 2.920 GB | very large, extremely low quality loss |
58
  | [Phi-3-mini-4k-instruct-Q8_0.gguf](https://huggingface.co/tensorblock/Phi-3-mini-4k-instruct-GGUF/tree/main/Phi-3-mini-4k-instruct-Q8_0.gguf) | Q8_0 | 3.782 GB | very large, extremely low quality loss - not recommended |
59