Transformers
English
Inference Endpoints
jncraton commited on
Commit
5a00b33
•
1 Parent(s): e71d673

Upload folder using huggingface_hub

Browse files
Files changed (6) hide show
  1. README.md +9 -12
  2. model.bin +2 -2
  3. special_tokens_map.json +3 -21
  4. tokenizer.json +20 -2
  5. tokenizer_config.json +53 -23
  6. vocabulary.json +3 -1
README.md CHANGED
@@ -3,7 +3,7 @@ license: apache-2.0
3
  datasets:
4
  - cerebras/SlimPajama-627B
5
  - bigcode/starcoderdata
6
- - timdettmers/openassistant-guanaco
7
  language:
8
  - en
9
  ---
@@ -16,23 +16,20 @@ https://github.com/jzhang38/TinyLlama
16
 
17
  The TinyLlama project aims to **pretrain** a **1.1B Llama model on 3 trillion tokens**. With some proper optimization, we can achieve this within a span of "just" 90 days using 16 A100-40G GPUs 🚀🚀. The training has started on 2023-09-01.
18
 
19
- <div align="center">
20
- <img src="./TinyLlama_logo.png" width="300"/>
21
- </div>
22
 
23
  We adopted exactly the same architecture and tokenizer as Llama 2. This means TinyLlama can be plugged and played in many open-source projects built upon Llama. Besides, TinyLlama is compact with only 1.1B parameters. This compactness allows it to cater to a multitude of applications demanding a restricted computation and memory footprint.
24
 
25
  #### This Model
26
- This is the chat model finetuned on [PY007/TinyLlama-1.1B-intermediate-step-240k-503b](https://huggingface.co/PY007/TinyLlama-1.1B-intermediate-step-240k-503b). The dataset used is [openassistant-guananco](https://huggingface.co/datasets/timdettmers/openassistant-guanaco).
27
-
28
  #### How to use
29
  You will need the transformers>=4.31
30
  Do check the [TinyLlama](https://github.com/jzhang38/TinyLlama) github page for more information.
31
- ```python
32
  from transformers import AutoTokenizer
33
  import transformers
34
  import torch
35
- model = "PY007/TinyLlama-1.1B-Chat-v0.1"
36
  tokenizer = AutoTokenizer.from_pretrained(model)
37
  pipeline = transformers.pipeline(
38
  "text-generation",
@@ -41,9 +38,9 @@ pipeline = transformers.pipeline(
41
  device_map="auto",
42
  )
43
 
44
- prompt = "What are the values in open source projects?"
45
  formatted_prompt = (
46
- f"### Human: {prompt}### Assistant:"
47
  )
48
 
49
 
@@ -51,10 +48,10 @@ sequences = pipeline(
51
  formatted_prompt,
52
  do_sample=True,
53
  top_k=50,
54
- top_p = 0.7,
55
  num_return_sequences=1,
56
  repetition_penalty=1.1,
57
- max_new_tokens=500,
58
  )
59
  for seq in sequences:
60
  print(f"Result: {seq['generated_text']}")
 
3
  datasets:
4
  - cerebras/SlimPajama-627B
5
  - bigcode/starcoderdata
6
+ - OpenAssistant/oasst_top1_2023-08-25
7
  language:
8
  - en
9
  ---
 
16
 
17
  The TinyLlama project aims to **pretrain** a **1.1B Llama model on 3 trillion tokens**. With some proper optimization, we can achieve this within a span of "just" 90 days using 16 A100-40G GPUs 🚀🚀. The training has started on 2023-09-01.
18
 
 
 
 
19
 
20
  We adopted exactly the same architecture and tokenizer as Llama 2. This means TinyLlama can be plugged and played in many open-source projects built upon Llama. Besides, TinyLlama is compact with only 1.1B parameters. This compactness allows it to cater to a multitude of applications demanding a restricted computation and memory footprint.
21
 
22
  #### This Model
23
+ This is the chat model finetuned on top of [PY007/TinyLlama-1.1B-intermediate-step-480k-1T](https://huggingface.co/PY007/TinyLlama-1.1B-intermediate-step-480k-1T).
24
+ The dataset used is [OpenAssistant/oasst_top1_2023-08-25](https://huggingface.co/datasets/OpenAssistant/oasst_top1_2023-08-25) following the [chatml](https://github.com/openai/openai-python/blob/main/chatml.md) format.
25
  #### How to use
26
  You will need the transformers>=4.31
27
  Do check the [TinyLlama](https://github.com/jzhang38/TinyLlama) github page for more information.
28
+ ```
29
  from transformers import AutoTokenizer
30
  import transformers
31
  import torch
32
+ model = "PY007/TinyLlama-1.1B-Chat-v0.3"
33
  tokenizer = AutoTokenizer.from_pretrained(model)
34
  pipeline = transformers.pipeline(
35
  "text-generation",
 
38
  device_map="auto",
39
  )
40
 
41
+ prompt = "How to get in a good university?"
42
  formatted_prompt = (
43
+ f"<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n"
44
  )
45
 
46
 
 
48
  formatted_prompt,
49
  do_sample=True,
50
  top_k=50,
51
+ top_p = 0.9,
52
  num_return_sequences=1,
53
  repetition_penalty=1.1,
54
+ max_new_tokens=1024,
55
  )
56
  for seq in sequences:
57
  print(f"Result: {seq['generated_text']}")
model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:71b5ffae759f0a4f0d85b5ff20bdc36fbd14167fa439da58af4e597f9d05f8bc
3
- size 1102182891
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:89eef765f34bef31eab7e1ec4a1c9209d75d702e322eb29ae1926b477eb1b821
3
+ size 1102191099
special_tokens_map.json CHANGED
@@ -1,24 +1,6 @@
1
  {
2
- "bos_token": {
3
- "content": "<s>",
4
- "lstrip": false,
5
- "normalized": false,
6
- "rstrip": false,
7
- "single_word": false
8
- },
9
- "eos_token": {
10
- "content": "</s>",
11
- "lstrip": false,
12
- "normalized": false,
13
- "rstrip": false,
14
- "single_word": false
15
- },
16
  "pad_token": "[PAD]",
17
- "unk_token": {
18
- "content": "<unk>",
19
- "lstrip": false,
20
- "normalized": false,
21
- "rstrip": false,
22
- "single_word": false
23
- }
24
  }
 
1
  {
2
+ "bos_token": "<s>",
3
+ "eos_token": "</s>",
 
 
 
 
 
 
 
 
 
 
 
 
4
  "pad_token": "[PAD]",
5
+ "unk_token": "<unk>"
 
 
 
 
 
 
6
  }
tokenizer.json CHANGED
@@ -34,10 +34,28 @@
34
  "id": 32000,
35
  "content": "[PAD]",
36
  "single_word": false,
37
- "lstrip": false,
38
- "rstrip": false,
39
  "normalized": false,
40
  "special": true
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
41
  }
42
  ],
43
  "normalizer": {
 
34
  "id": 32000,
35
  "content": "[PAD]",
36
  "single_word": false,
37
+ "lstrip": true,
38
+ "rstrip": true,
39
  "normalized": false,
40
  "special": true
41
+ },
42
+ {
43
+ "id": 32001,
44
+ "content": "<|im_start|>",
45
+ "single_word": false,
46
+ "lstrip": false,
47
+ "rstrip": false,
48
+ "normalized": true,
49
+ "special": false
50
+ },
51
+ {
52
+ "id": 32002,
53
+ "content": "<|im_end|>",
54
+ "single_word": false,
55
+ "lstrip": false,
56
+ "rstrip": false,
57
+ "normalized": true,
58
+ "special": false
59
  }
60
  ],
61
  "normalizer": {
tokenizer_config.json CHANGED
@@ -1,34 +1,64 @@
1
  {
2
- "bos_token": {
3
- "__type": "AddedToken",
4
- "content": "<s>",
5
- "lstrip": false,
6
- "normalized": false,
7
- "rstrip": false,
8
- "single_word": false
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9
  },
 
 
10
  "clean_up_tokenization_spaces": false,
11
- "eos_token": {
12
- "__type": "AddedToken",
13
- "content": "</s>",
14
- "lstrip": false,
15
- "normalized": false,
16
- "rstrip": false,
17
- "single_word": false
18
- },
19
  "legacy": false,
20
  "model_max_length": 1000000000000000019884624838656,
21
  "pad_token": null,
22
  "padding_side": "right",
23
  "sp_model_kwargs": {},
24
  "tokenizer_class": "LlamaTokenizer",
25
- "unk_token": {
26
- "__type": "AddedToken",
27
- "content": "<unk>",
28
- "lstrip": false,
29
- "normalized": false,
30
- "rstrip": false,
31
- "single_word": false
32
- },
33
  "use_default_system_prompt": true
34
  }
 
1
  {
2
+ "added_tokens_decoder": {
3
+ "0": {
4
+ "content": "<unk>",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false,
9
+ "special": true
10
+ },
11
+ "1": {
12
+ "content": "<s>",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false,
17
+ "special": true
18
+ },
19
+ "2": {
20
+ "content": "</s>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": true
26
+ },
27
+ "32000": {
28
+ "content": "[PAD]",
29
+ "lstrip": true,
30
+ "normalized": false,
31
+ "rstrip": true,
32
+ "single_word": false,
33
+ "special": true
34
+ },
35
+ "32001": {
36
+ "content": "<|im_start|>",
37
+ "lstrip": false,
38
+ "normalized": true,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": false
42
+ },
43
+ "32002": {
44
+ "content": "<|im_end|>",
45
+ "lstrip": false,
46
+ "normalized": true,
47
+ "rstrip": false,
48
+ "single_word": false,
49
+ "special": false
50
+ }
51
  },
52
+ "additional_special_tokens": [],
53
+ "bos_token": "<s>",
54
  "clean_up_tokenization_spaces": false,
55
+ "eos_token": "</s>",
 
 
 
 
 
 
 
56
  "legacy": false,
57
  "model_max_length": 1000000000000000019884624838656,
58
  "pad_token": null,
59
  "padding_side": "right",
60
  "sp_model_kwargs": {},
61
  "tokenizer_class": "LlamaTokenizer",
62
+ "unk_token": "<unk>",
 
 
 
 
 
 
 
63
  "use_default_system_prompt": true
64
  }
vocabulary.json CHANGED
@@ -31999,5 +31999,7 @@
31999
  "\u6536",
32000
  "\u5f18",
32001
  "\u7ed9",
32002
- "[PAD]"
 
 
32003
  ]
 
31999
  "\u6536",
32000
  "\u5f18",
32001
  "\u7ed9",
32002
+ "[PAD]",
32003
+ "<|im_start|>",
32004
+ "<|im_end|>"
32005
  ]