Upload folder using huggingface_hub

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "word_embedding_dimension": 896,
+  "pooling_mode_cls_token": false,
+  "pooling_mode_mean_tokens": true,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false,
+  "include_prompt": true
+}

README.md

@@ -0,0 +1,463 @@
+---
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- generated_from_trainer
+- dataset_size:21769
+- loss:MultipleNegativesRankingLoss
+base_model: am-azadi/KaLM-embedding-multilingual-mini-v1_Fine_Tuned_1e
+widget:
+- source_sentence: Day 1 - Job Losses Biden CANCELS Keystone Pipeline on - Day 1.
+    XX 83k jobs lost. XX Get ready for $4 Gas prices by Summer.
+  sentences:
+  - Pedro Castillo manipulated a photograph of a rally Photo of a Castillo rally in
+    Peru was altered to show alleged manipulation
+  - Biden's Keystone XL pipeline reversal will cost tens of thousands of jobs Posts
+    inflate job losses from Biden's Keystone pipeline reversal
+  - Delete System32 folder to clear your privacy browsing history? This hoax has been
+    around for years, don’t delete System32 folder
+- source_sentence: ' Thiago Brazil  The "Russian missile" turns cars and destroys
+    the street but the windows of the buildings did not break down and neither did
+    smeared with dust. 1 more fake advertising piece of the neo-Nazi Zelensky. need
+    do more next time!!'
+  sentences:
+  - Intact windows in Ukraine prove Russian attack simulation Intact windows and overturned
+    cars do not prove simulated attack in Bucha, Ukraine
+  - Editorial of the newspaper Le Monde says that Mexico is on the way to ruin The
+    newspaper Le Monde did not publish an editorial titled "Mexico on a direct path
+    to ruin"
+  - A photo of 189-year-old Jonathan the turtle This photo does not show the 189-year-old
+    Jonathan tortoise, but a giant tortoise in Australia
+- source_sentence: ' madri Greta Thunberg, urged the Chinese to do without traditional
+    chopsticks to protect the trees The Chinese then asked Greta to return to the
+    school she was in could find out that traditional Chopsticks are made from bamboo,
+    and bamboo is a grass! The Chinese have Greta and her friends too asked to give
+    up toilet paper to wipe her ass ''cause this one will made from trees.'
+  sentences:
+  - This is how they repress in Bolivia tear gas grenade to the head The man killed
+    by the shot of a tear gas grenade to the head was the victim of the repression
+    of a protest in Iraq, not in Bolivia
+  - Greta Thunberg urged China to ban chopsticks There is no evidence for Greta Thunberg's
+    demand for a ban on chopsticks
+  - Accurate reporting on Pfizer-BioNTech Covid-19 vaccination drive and deaths in
+    Germany Social media posts misrepresent Pfizer-BioNTech Covid-19 vaccinations
+    in Germany
+- source_sentence: Do you want to know the truth? The "Vaccine" they are voting for
+    is mRNA, it circulates through the blood until it finds a receptor for the enzyme
+    ACE2, which exists mainly in the testicles, a little in the ovaries, and in the
+    myelin of neurons. The m is for messenger, through the receptor, the RNA penetrates
+    the cell and rewrites its genetic code. The cell no longer serves what nature
+    created it for, it serves to create what the laboratories designed RNA for. Theoretically
+    "defenses". The price is that 97% of the inoculated males will remain sterile,
+    but also, if they are young children, they will never develop secondary sexual
+    characteristics. They will be androgynous, without sexual desire, or very moderate,
+    and probably more manageable and obedient. 45% of girls will be sterile. Neuronal
+    damage, on the other hand, will affect part of your frontal cortex. You will be
+    able to work, even drive a car, but not think deeply. Perfect slaves of the New
+    Normality. It is PHASE 3 of the plan, as it was finalized in EVENT 201. PHASE
+    1 was to scare you, isolate you and lock you up, due to a virus that, as a single
+    cause, only killed a tiny handful of people. Much less than last year's flu. PHASE
+    2 makes you wear a grotesque and useless mask, which depersonalizes you and deprives
+    you of oxygen. May you lose your job, partner and affections. PHASE 3, when you
+    are already desperate, is the "Vaccine". They're going to tell you I'm lying,
+    so ask what's in it. They will answer that by law not even doctors can know. Secret.
+    You don't have the maturity to know it, trust the government, the media, the WHO
+    and the employees of George Soros and Bill Gates, like Dr. Pedro Cahn and his
+    sinister Fundación Huésped. They will tell you that the laboratories are responsible,
+    but by law you will not be able to claim anyone. Let's see, when your balls dry,
+    you'll only have to cry about what's left of them. When you know that you will
+    never have a grandchild, that you will never see your son become a father, nor
+    graduate from a career, because his brain will be lobotomized. The opposition"?
+    I don't want to make you bitter, but 90% receive money from Soros' Open Society,
+    from the Bill and Melinda Gates Foundation, from the Ford Foundation, from the
+    Rockefeller Foundation, from the Chinese Communist Party through its figurehead,
+    the investor Ming Wai Lau. Who will tell you the truth? Dr. Roxana Bruno, Dr.
+    Chinda Brandolino, Dr. Heiko Schöning, Doctors for Truth, Lawyers for Truth, Teachers
+    for Truth. Turn off the TV, burn your muzzle, breathe, go out to hug your parents,
+    embrace freedom, don't let any doctor who isn't the truth touch you. In this way
+    the Global Sanitary Dictatorship will collapse, and we will wake up from this
+    nightmare. From the wall of Horacio Rivara CLIPARTO CLIPARTO CLIPARTO CLIPARTO
+    CLIPARTO CLIPARTO C C
+  sentences:
+  - Today- Mayor of São Paulo thanking the Bolsonaro government on vaccines against
+    covid-19 Video with thanks to the federal government was for funds for a hospital
+    in May 2020
+  - This photo shows Bolsonaro surrounded by global leaders at a G20 meeting No, the
+    photo is a montage and who appears in the original is US President Donald Trump
+  - Vaccines to prevent covid-19 cause infertility Vaccines to prevent covid-19 are
+    not designed to affect fertility
+- source_sentence: 'The moment of the death of President Mohamed Morsi, may God have
+    mercy on him, God willing '
+  sentences:
+  - Cuba has Interferon Alpha 2B, the cure, the vaccine against the coronavirus The
+    Cuban antiviral Interferon Alfa 2B is used in China to treat patients with the
+    new coronavirus, but it is neither a vaccine nor a cure
+  - 'José Antonio Kast said: "Juvenile delinquent of 16 or 17 years will not go to
+    sename, he will do compulsory military service" Chilean presidential candidate
+    Kast does not propose that young people who commit crimes do military service'
+  - The moment of the death of President Mohamed Morsi This video belongs to the trial
+    of those accused of the Port Said events and does not show the moment of the death
+    of former Egyptian President Mohamed Morsi
+pipeline_tag: sentence-similarity
+library_name: sentence-transformers
+---
+
+# SentenceTransformer based on am-azadi/KaLM-embedding-multilingual-mini-v1_Fine_Tuned_1e
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [am-azadi/KaLM-embedding-multilingual-mini-v1_Fine_Tuned_1e](https://huggingface.co/am-azadi/KaLM-embedding-multilingual-mini-v1_Fine_Tuned_1e). It maps sentences & paragraphs to a 896-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
+
+## Model Details
+
+### Model Description
+- **Model Type:** Sentence Transformer
+- **Base model:** [am-azadi/KaLM-embedding-multilingual-mini-v1_Fine_Tuned_1e](https://huggingface.co/am-azadi/KaLM-embedding-multilingual-mini-v1_Fine_Tuned_1e) <!-- at revision db90e52b2078421f04b71e31b5a90f5bf8d321d7 -->
+- **Maximum Sequence Length:** 512 tokens
+- **Output Dimensionality:** 896 dimensions
+- **Similarity Function:** Cosine Similarity
+<!-- - **Training Dataset:** Unknown -->
+<!-- - **Language:** Unknown -->
+<!-- - **License:** Unknown -->
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
+- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
+
+### Full Model Architecture
+
+```
+SentenceTransformer(
+  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: Qwen2Model 
+  (1): Pooling({'word_embedding_dimension': 896, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
+  (2): Normalize()
+)
+```
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+
+Then you can load this model and run inference.
+```python
+from sentence_transformers import SentenceTransformer
+
+# Download from the 🤗 Hub
+model = SentenceTransformer("sentence_transformers_model_id")
+# Run inference
+sentences = [
+    'The moment of the death of President Mohamed Morsi, may God have mercy on him, God willing ',
+    'The moment of the death of President Mohamed Morsi This video belongs to the trial of those accused of the Port Said events and does not show the moment of the death of former Egyptian President Mohamed Morsi',
+    'Cuba has Interferon Alpha 2B, the cure, the vaccine against the coronavirus The Cuban antiviral Interferon Alfa 2B is used in China to treat patients with the new coronavirus, but it is neither a vaccine nor a cure',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 896]
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities.shape)
+# [3, 3]
+```
+
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+* Size: 21,769 training samples
+* Columns: <code>sentence_0</code> and <code>sentence_1</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | sentence_0                                                                         | sentence_1                                                                          |
+  |:--------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|
+  | type    | string                                                                             | string                                                                              |
+  | details | <ul><li>min: 4 tokens</li><li>mean: 109.9 tokens</li><li>max: 512 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 34.57 tokens</li><li>max: 132 tokens</li></ul> |
+* Samples:
+  | sentence_0                                                                                                                                                                                                                                                                        | sentence_1                                                                                                                                                                                                                           |
+  |:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>Sad, and we are hostages!! If that doesn't make you think about the “measures” that governors and mayors are taking there is nothing that can be made in Brazil</code>                                                                                                      | <code>Action by a military police officer against a street vendor amid restrictive measures due to the covid-19 pandemic The photo in which a PM seizes products from a street vendor is from 2016, unrelated to the pandemic</code> |
+  | <code> This is why it's important to know your history d4 Rare photo of Queen Elizabeth II and Prince Phillip bowing before the real original African Royalty, Empress Menen Asfaw and her husband Emperor Ras Tafari Makonnen Woldemikael Haile Selassie I of Ethiopia...</code> | <code>Queen Elizabeth II bows before Ethiopian Emperor Haile Selassie British monarch's first visit to Ethiopia came 10 years after this photo was taken</code>                                                                      |
+  | <code>Public Reaction on Hyderabad Priyanka Reddy Case Drabad Encounter . Common people say</code>                                                                                                                                                                                | <code>Photo of suspects killed by police in Hyderabad rape-murder case This photo has circulated online since at least 2015 in connection with an unrelated case in a different Indian state</code>                                  |
+* Loss: [<code>MultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "cos_sim"
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `per_device_train_batch_size`: 2
+- `per_device_eval_batch_size`: 2
+- `num_train_epochs`: 1
+- `multi_dataset_batch_sampler`: round_robin
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: no
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 2
+- `per_device_eval_batch_size`: 2
+- `per_gpu_train_batch_size`: None
+- `per_gpu_eval_batch_size`: None
+- `gradient_accumulation_steps`: 1
+- `eval_accumulation_steps`: None
+- `torch_empty_cache_steps`: None
+- `learning_rate`: 5e-05
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1
+- `num_train_epochs`: 1
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.0
+- `warmup_steps`: 0
+- `log_level`: passive
+- `log_level_replica`: warning
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `save_safetensors`: True
+- `save_on_each_node`: False
+- `save_only_model`: False
+- `restore_callback_states_from_checkpoint`: False
+- `no_cuda`: False
+- `use_cpu`: False
+- `use_mps_device`: False
+- `seed`: 42
+- `data_seed`: None
+- `jit_mode_eval`: False
+- `use_ipex`: False
+- `bf16`: False
+- `fp16`: False
+- `fp16_opt_level`: O1
+- `half_precision_backend`: auto
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `local_rank`: 0
+- `ddp_backend`: None
+- `tpu_num_cores`: None
+- `tpu_metrics_debug`: False
+- `debug`: []
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 0
+- `dataloader_prefetch_factor`: None
+- `past_index`: -1
+- `disable_tqdm`: False
+- `remove_unused_columns`: True
+- `label_names`: None
+- `load_best_model_at_end`: False
+- `ignore_data_skip`: False
+- `fsdp`: []
+- `fsdp_min_num_params`: 0
+- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
+- `fsdp_transformer_layer_cls_to_wrap`: None
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `deepspeed`: None
+- `label_smoothing_factor`: 0.0
+- `optim`: adamw_torch
+- `optim_args`: None
+- `adafactor`: False
+- `group_by_length`: False
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `skip_memory_metrics`: True
+- `use_legacy_prediction_loop`: False
+- `push_to_hub`: False
+- `resume_from_checkpoint`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_private_repo`: None
+- `hub_always_push`: False
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `include_inputs_for_metrics`: False
+- `include_for_metrics`: []
+- `eval_do_concat_batches`: True
+- `fp16_backend`: auto
+- `push_to_hub_model_id`: None
+- `push_to_hub_organization`: None
+- `mp_parameters`: 
+- `auto_find_batch_size`: False
+- `full_determinism`: False
+- `torchdynamo`: None
+- `ray_scope`: last
+- `ddp_timeout`: 1800
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `dispatch_batches`: None
+- `split_batches`: None
+- `include_tokens_per_second`: False
+- `include_num_input_tokens_seen`: False
+- `neftune_noise_alpha`: None
+- `optim_target_modules`: None
+- `batch_eval_metrics`: False
+- `eval_on_start`: False
+- `use_liger_kernel`: False
+- `eval_use_gather_object`: False
+- `average_tokens_across_devices`: False
+- `prompts`: None
+- `batch_sampler`: batch_sampler
+- `multi_dataset_batch_sampler`: round_robin
+
+</details>
+
+### Training Logs
+| Epoch  | Step  | Training Loss |
+|:------:|:-----:|:-------------:|
+| 0.0459 | 500   | 0.0083        |
+| 0.0919 | 1000  | 0.019         |
+| 0.1378 | 1500  | 0.0255        |
+| 0.1837 | 2000  | 0.0372        |
+| 0.2297 | 2500  | 0.0315        |
+| 0.2756 | 3000  | 0.0258        |
+| 0.3215 | 3500  | 0.0211        |
+| 0.3675 | 4000  | 0.0187        |
+| 0.4134 | 4500  | 0.0264        |
+| 0.4593 | 5000  | 0.0348        |
+| 0.5053 | 5500  | 0.0197        |
+| 0.5512 | 6000  | 0.0102        |
+| 0.5972 | 6500  | 0.0092        |
+| 0.6431 | 7000  | 0.0169        |
+| 0.6890 | 7500  | 0.0109        |
+| 0.7350 | 8000  | 0.0115        |
+| 0.7809 | 8500  | 0.0173        |
+| 0.8268 | 9000  | 0.0196        |
+| 0.8728 | 9500  | 0.028         |
+| 0.9187 | 10000 | 0.0218        |
+| 0.9646 | 10500 | 0.0169        |
+| 0.0459 | 500   | 0.004         |
+| 0.0919 | 1000  | 0.02          |
+| 0.1378 | 1500  | 0.0154        |
+| 0.1837 | 2000  | 0.0141        |
+| 0.2297 | 2500  | 0.014         |
+| 0.2756 | 3000  | 0.0077        |
+| 0.3215 | 3500  | 0.018         |
+| 0.3675 | 4000  | 0.0079        |
+| 0.4134 | 4500  | 0.0238        |
+| 0.4593 | 5000  | 0.0183        |
+| 0.5053 | 5500  | 0.0159        |
+| 0.5512 | 6000  | 0.0043        |
+| 0.5972 | 6500  | 0.0066        |
+| 0.6431 | 7000  | 0.0068        |
+| 0.6890 | 7500  | 0.0035        |
+| 0.7350 | 8000  | 0.0042        |
+| 0.7809 | 8500  | 0.0084        |
+| 0.8268 | 9000  | 0.0049        |
+| 0.8728 | 9500  | 0.0102        |
+| 0.9187 | 10000 | 0.0048        |
+| 0.9646 | 10500 | 0.0045        |
+
+
+### Framework Versions
+- Python: 3.11.11
+- Sentence Transformers: 3.4.1
+- Transformers: 4.48.3
+- PyTorch: 2.5.1+cu124
+- Accelerate: 1.3.0
+- Datasets: 3.3.2
+- Tokenizers: 0.21.0
+
+## Citation
+
+### BibTeX
+
+#### Sentence Transformers
+```bibtex
+@inproceedings{reimers-2019-sentence-bert,
+    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
+    author = "Reimers, Nils and Gurevych, Iryna",
+    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
+    month = "11",
+    year = "2019",
+    publisher = "Association for Computational Linguistics",
+    url = "https://arxiv.org/abs/1908.10084",
+}
+```
+
+#### MultipleNegativesRankingLoss
+```bibtex
+@misc{henderson2017efficient,
+    title={Efficient Natural Language Response Suggestion for Smart Reply},
+    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
+    year={2017},
+    eprint={1705.00652},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

added_tokens.json

@@ -0,0 +1,5 @@
+{
+  "<|endoftext|>": 151643,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644
+}

config.json

@@ -0,0 +1,29 @@
+{
+  "_name_or_path": "am-azadi/KaLM-embedding-multilingual-mini-v1_Fine_Tuned_1e",
+  "architectures": [
+    "Qwen2Model"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 896,
+  "initializer_range": 0.02,
+  "intermediate_size": 4864,
+  "max_position_embeddings": 131072,
+  "max_window_layers": 24,
+  "model_type": "qwen2",
+  "num_attention_heads": 14,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 2,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.48.3",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

config_sentence_transformers.json

@@ -0,0 +1,13 @@
+{
+  "__version__": {
+    "sentence_transformers": "3.4.1",
+    "transformers": "4.48.3",
+    "pytorch": "2.5.1+cu124"
+  },
+  "prompts": {
+    "query": "",
+    "document": ""
+  },
+  "default_prompt_name": null,
+  "similarity_fn_name": "cosine"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e2213f66a3569b4a5ad7a214cc411d38c55182a2dae8de135a61b0a13e6814d9
+size 1976161736

modules.json

@@ -0,0 +1,20 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.models.Normalize"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 512,
+  "do_lower_case": false
+}

special_tokens_map.json

@@ -0,0 +1,20 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "eos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c8eab352ec6bb19236f8684bf40e504e86876bd4f2f43982b0561b2f07702666
+size 11418805

tokenizer_config.json

@@ -0,0 +1,57 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "auto_map": {
+    "AutoTokenizer": [
+      "HIT-TMG/KaLM-embedding-multilingual-mini-v1--tokenization_qwen.Qwen2Tokenizer",
+      "HIT-TMG/KaLM-embedding-multilingual-mini-v1--tokenization_qwen.Qwen2TokenizerFast"
+    ]
+  },
+  "bos_token": null,
+  "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "max_length": 512,
+  "model_max_length": 512,
+  "pad_to_multiple_of": null,
+  "pad_token": "<|endoftext|>",
+  "pad_token_type_id": 0,
+  "padding_side": "left",
+  "split_special_tokens": false,
+  "stride": 0,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": null
+}