CharlesCGCTG commited on
Commit
2f89eea
1 Parent(s): cc1f610

Upload folder using huggingface_hub

Browse files
README.md ADDED
@@ -0,0 +1,67 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - merge
4
+ - mergekit
5
+ - lazymergekit
6
+ - CGCTG/camembert-base_jina-embeddings-v2-small-en_fr
7
+ - CGCTG/distilcamembert-base_jina-embeddings-v2-small-en_fr
8
+ base_model:
9
+ - CGCTG/camembert-base_jina-embeddings-v2-small-en_fr
10
+ - CGCTG/distilcamembert-base_jina-embeddings-v2-small-en_fr
11
+ ---
12
+
13
+ # Cam_DistilCamembert_FR_SLERP
14
+
15
+ Cam_DistilCamembert_FR_SLERP is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
16
+ * [CGCTG/camembert-base_jina-embeddings-v2-small-en_fr](https://huggingface.co/CGCTG/camembert-base_jina-embeddings-v2-small-en_fr)
17
+ * [CGCTG/distilcamembert-base_jina-embeddings-v2-small-en_fr](https://huggingface.co/CGCTG/distilcamembert-base_jina-embeddings-v2-small-en_fr)
18
+
19
+ ## 🧩 Configuration
20
+
21
+ ```yaml
22
+ slices:
23
+ - sources:
24
+ - model: CGCTG/camembert-base_jina-embeddings-v2-small-en_fr
25
+ layer_range: [0, 4]
26
+ - model: CGCTG/distilcamembert-base_jina-embeddings-v2-small-en_fr
27
+ layer_range: [0, 4]
28
+ # or, the equivalent models: syntax:
29
+ #models:
30
+ # - model: ClassCat/gpt2-base-french
31
+ # - model: cmarkea/distilcamembert-base
32
+ merge_method: slerp
33
+ base_model: CGCTG/camembert-base_jina-embeddings-v2-small-en_fr
34
+ parameters:
35
+ t:
36
+ - filter: self_attn
37
+ value: [0, 0.5, 0.3, 0.7, 1]
38
+ - filter: mlp
39
+ value: [1, 0.5, 0.7, 0.3, 0]
40
+ - value: 0.5 # fallback for rest of tensors
41
+ dtype: float16
42
+ ```
43
+
44
+ ## 💻 Usage
45
+
46
+ ```python
47
+ !pip install -qU transformers accelerate
48
+
49
+ from transformers import AutoTokenizer
50
+ import transformers
51
+ import torch
52
+
53
+ model = "CGCTG/Cam_DistilCamembert_FR_SLERP"
54
+ messages = [{"role": "user", "content": "What is a large language model?"}]
55
+
56
+ tokenizer = AutoTokenizer.from_pretrained(model)
57
+ prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
58
+ pipeline = transformers.pipeline(
59
+ "text-generation",
60
+ model=model,
61
+ torch_dtype=torch.float16,
62
+ device_map="auto",
63
+ )
64
+
65
+ outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
66
+ print(outputs[0]["generated_text"])
67
+ ```
config.json ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "CGCTG/camembert-base_jina-embeddings-v2-small-en_fr",
3
+ "architectures": [
4
+ "BertModel"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.0,
7
+ "attn_implementation": null,
8
+ "auto_map": {
9
+ "AutoConfig": "jinaai/jina-bert-implementation--configuration_bert.JinaBertConfig",
10
+ "AutoModel": "jinaai/jina-bert-implementation--modeling_bert.JinaBertModel",
11
+ "AutoModelForMaskedLM": "jinaai/jina-bert-implementation--modeling_bert.JinaBertForMaskedLM",
12
+ "AutoModelForSequenceClassification": "jinaai/jina-bert-implementation--modeling_bert.JinaBertForSequenceClassification"
13
+ },
14
+ "classifier_dropout": null,
15
+ "emb_pooler": "mean",
16
+ "feed_forward_type": "geglu",
17
+ "gradient_checkpointing": false,
18
+ "hidden_act": "gelu",
19
+ "hidden_dropout_prob": 0.1,
20
+ "hidden_size": 512,
21
+ "initializer_range": 0.02,
22
+ "intermediate_size": 2048,
23
+ "layer_norm_eps": 1e-12,
24
+ "max_position_embeddings": 8192,
25
+ "model_max_length": 8192,
26
+ "model_type": "bert",
27
+ "num_attention_heads": 8,
28
+ "num_hidden_layers": 4,
29
+ "pad_token_id": 0,
30
+ "position_embedding_type": "alibi",
31
+ "torch_dtype": "float16",
32
+ "transformers_version": "4.41.0",
33
+ "type_vocab_size": 2,
34
+ "use_cache": true,
35
+ "vocab_size": 30528
36
+ }
mergekit_config.yml ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+ slices:
3
+ - sources:
4
+ - model: CGCTG/camembert-base_jina-embeddings-v2-small-en_fr
5
+ layer_range: [0, 4]
6
+ - model: CGCTG/distilcamembert-base_jina-embeddings-v2-small-en_fr
7
+ layer_range: [0, 4]
8
+ # or, the equivalent models: syntax:
9
+ #models:
10
+ # - model: ClassCat/gpt2-base-french
11
+ # - model: cmarkea/distilcamembert-base
12
+ merge_method: slerp
13
+ base_model: CGCTG/camembert-base_jina-embeddings-v2-small-en_fr
14
+ parameters:
15
+ t:
16
+ - filter: self_attn
17
+ value: [0, 0.5, 0.3, 0.7, 1]
18
+ - filter: mlp
19
+ value: [1, 0.5, 0.7, 0.3, 0]
20
+ - value: 0.5 # fallback for rest of tensors
21
+ dtype: float16
model-00001-of-00001.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1a8cd6b5de4235652e4e8df40f0d584aff58994229d1f8fb60c329081d6ddde7
3
+ size 65405552
model.safetensors.index.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"metadata": {"mergekit_version": "0.0.4.2", "total_size": 65397760}, "weight_map": {"embeddings.LayerNorm.bias": "model-00001-of-00001.safetensors", "embeddings.LayerNorm.weight": "model-00001-of-00001.safetensors", "embeddings.position_embeddings.weight": "model-00001-of-00001.safetensors", "embeddings.token_type_embeddings.weight": "model-00001-of-00001.safetensors", "embeddings.word_embeddings.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.output.LayerNorm.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.output.LayerNorm.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.output.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.output.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.self.key.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.self.key.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.self.query.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.self.query.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.self.value.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.attention.self.value.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.intermediate.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.intermediate.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.output.LayerNorm.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.output.LayerNorm.weight": "model-00001-of-00001.safetensors", "encoder.layer.0.output.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.0.output.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.output.LayerNorm.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.output.LayerNorm.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.output.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.output.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.self.key.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.self.key.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.self.query.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.self.query.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.self.value.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.attention.self.value.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.intermediate.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.intermediate.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.output.LayerNorm.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.output.LayerNorm.weight": "model-00001-of-00001.safetensors", "encoder.layer.1.output.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.1.output.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.output.LayerNorm.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.output.LayerNorm.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.output.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.output.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.self.key.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.self.key.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.self.query.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.self.query.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.self.value.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.attention.self.value.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.intermediate.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.intermediate.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.output.LayerNorm.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.output.LayerNorm.weight": "model-00001-of-00001.safetensors", "encoder.layer.2.output.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.2.output.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.3.attention.output.LayerNorm.bias": "model-00001-of-00001.safetensors", "encoder.layer.3.attention.output.LayerNorm.weight": "model-00001-of-00001.safetensors", "encoder.layer.3.attention.output.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.3.attention.output.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.3.attention.self.key.bias": "model-00001-of-00001.safetensors", "encoder.layer.3.attention.self.key.weight": "model-00001-of-00001.safetensors", "encoder.layer.3.attention.self.query.bias": "model-00001-of-00001.safetensors", "encoder.layer.3.attention.self.query.weight": "model-00001-of-00001.safetensors", "encoder.layer.3.attention.self.value.bias": "model-00001-of-00001.safetensors", "encoder.layer.3.attention.self.value.weight": "model-00001-of-00001.safetensors", "encoder.layer.3.intermediate.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.3.intermediate.dense.weight": "model-00001-of-00001.safetensors", "encoder.layer.3.output.LayerNorm.bias": "model-00001-of-00001.safetensors", "encoder.layer.3.output.LayerNorm.weight": "model-00001-of-00001.safetensors", "encoder.layer.3.output.dense.bias": "model-00001-of-00001.safetensors", "encoder.layer.3.output.dense.weight": "model-00001-of-00001.safetensors", "pooler.dense.bias": "model-00001-of-00001.safetensors", "pooler.dense.weight": "model-00001-of-00001.safetensors"}}
special_tokens_map.json ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "cls_token": {
3
+ "content": "[CLS]",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "mask_token": {
10
+ "content": "[MASK]",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": {
17
+ "content": "[PAD]",
18
+ "lstrip": false,
19
+ "normalized": false,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ },
23
+ "sep_token": {
24
+ "content": "[SEP]",
25
+ "lstrip": false,
26
+ "normalized": false,
27
+ "rstrip": false,
28
+ "single_word": false
29
+ },
30
+ "unk_token": {
31
+ "content": "[UNK]",
32
+ "lstrip": false,
33
+ "normalized": false,
34
+ "rstrip": false,
35
+ "single_word": false
36
+ }
37
+ }
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
@@ -0,0 +1,64 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "added_tokens_decoder": {
3
+ "0": {
4
+ "content": "[PAD]",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false,
9
+ "special": true
10
+ },
11
+ "100": {
12
+ "content": "[UNK]",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false,
17
+ "special": true
18
+ },
19
+ "101": {
20
+ "content": "[CLS]",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": true
26
+ },
27
+ "102": {
28
+ "content": "[SEP]",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": true
34
+ },
35
+ "103": {
36
+ "content": "[MASK]",
37
+ "lstrip": false,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ }
43
+ },
44
+ "clean_up_tokenization_spaces": true,
45
+ "cls_token": "[CLS]",
46
+ "do_basic_tokenize": true,
47
+ "do_lower_case": true,
48
+ "mask_token": "[MASK]",
49
+ "max_length": 8192,
50
+ "model_max_length": 2147483648,
51
+ "never_split": null,
52
+ "pad_to_multiple_of": null,
53
+ "pad_token": "[PAD]",
54
+ "pad_token_type_id": 0,
55
+ "padding_side": "right",
56
+ "sep_token": "[SEP]",
57
+ "stride": 0,
58
+ "strip_accents": null,
59
+ "tokenize_chinese_chars": true,
60
+ "tokenizer_class": "BertTokenizer",
61
+ "truncation_side": "right",
62
+ "truncation_strategy": "longest_first",
63
+ "unk_token": "[UNK]"
64
+ }
vocab.txt ADDED
The diff for this file is too large to render. See raw diff