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Model: proxectonos/Carvalho-Salamandra-Instruct Source: Original Platform
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README.md
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---
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library_name: transformers
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license: mit
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language:
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- gl
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- pt
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- es
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- en
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- ca
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base_model:
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- BSC-LT/salamandra-7b-instruct
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pipeline_tag: text-generation
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tags:
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- Salamandra
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- Instruction-tuning
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- Multilingual
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datasets:
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- proxectonos/cpt_instruction_datasets
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---
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# Carvalho-Salamandra-Instruct
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> [!WARNING]
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> **WARNING:** This is a preliminary version of Carvalho-Salamandra-Instruct.
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## Table of Contents
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<details>
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<summary>Click to expand</summary>
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- [Carvalho-Salamandra-Instruct](#carvalho-salamandra-instruct)
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- [Table of Contents](#table-of-contents)
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- [Model description](#model-description)
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- [Intended uses and limitations](#intended-uses-and-limitations)
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- [How to use](#how-to-use)
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- [Training](#training)
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- [Tools](#tools)
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- [Training data](#training-data)
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- [Training hyperparameters](#training-hyperparameters)
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- [Framework](#framework)
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- [Evaluation](#evaluation)
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- [Additional information](#additional-information)
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- [Funding](#funding)
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- [Cite this model](#cite-this-model)
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</details>
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## Model description
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**Carvalho-Salamandra-Instruct** is a 7B-parameter instruction-tuned transformer model covering Galician, Portuguese, Spanish, English and Catalan.
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It is based on [BSC-LT/salamandra-7b-instruct](https://huggingface.co/BSC-LT/salamandra-7b-instruct) and was further adapted through a 1-epoch training run using high-quality multilingual corpora, with a marked emphasis on Galician and Portuguese.
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This model aims to provide strong instruction-following and generation capabilities for underrepresented languages while maintaining robust multilingual behavior.
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## Intended uses and limitations
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**Intended uses**
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- Instruction following and dialogue-style generation.
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- Multilingual text generation and content creation.
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- Downstream fine-tuning for tasks such as summarization, classification, or question answering (with appropriate supervised data).
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**Limitations**
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- Not intended as a sole source for high-stakes or safety-critical decisions.
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- May produce incorrect or biased factual information — verify outputs when accuracy matters.
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- Performance may vary by language and domain; best results in Galician and Portuguese given training emphasis.
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## How to use
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```python
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from datetime import datetime
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import transformers
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import torch
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model_id = "proxectonos/Carvalho-Salamandra-Instruct"
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text = "Qué sabes sobre o Proxecto Nós?"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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device_map="auto",
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torch_dtype=torch.bfloat16
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)
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message = [ { "role": "user", "content": text } ]
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date_string = datetime.today().strftime('%Y-%m-%d')
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prompt = tokenizer.apply_chat_template(
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message,
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tokenize=False,
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add_generation_prompt=True,
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date_string=date_string
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)
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inputs = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt")
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outputs = model.generate(input_ids=inputs.to(model.device), max_new_tokens=200)
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generated_tokens = outputs[0][len(inputs[0]):]
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response = self.tokenizer.decode(generated_tokens, skip_special_tokens=False).strip()
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response = response.split("<|reserved_token_1|>")[0].strip()
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print(response)
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```
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## Training
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### Training data
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The model was trained with a mix of instruction data and high-quality monolingual corpora, designed to maximize performance in Galician and Portuguese while preserving broad multilingual capabilities.
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| **Dataset Type** | **Languages** | **Tokens per language/Source** |
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|----------------------|------------------------------|------------|
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| Full instruction set | GL , ES , PT , CAT , EN | [Galician Instruction Datasets](https://github.com/proxectonos/instruction_datasets) |
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| High-quality corpus | GL, PT | 250M |
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| Small HQ corpus | EN, ES, CAT | 30M |
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### Training hyperparameters
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- **epochs:** 1
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- **dtype:** bf16
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- **block size:** 2048
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- **total batch size:** 128
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- **learning rate:** 2e-6
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- **scheduler:** Linear
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- **optimizations:**
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- gradient checkpointing: True
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- flash attention: True
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- liger kernels: True
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- DeepSpeed stage: 2
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### Framework
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Training was performed at the **Galician Supercomputing Center (CESGA)** using **2 nodes** (each with **2× NVIDIA A100 40GB**) — a total of **4 GPUs** — across **2 days**.
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## Evaluation
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Formal evaluation is ongoing. Preliminary internal tests show strong instruction-following ability and improved generation quality for Galician and Portuguese compared to the base model. Detailed benchmarks and quantitative results will be added when available.
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## Additional information
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## Funding
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This work is funded by the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the project Desarrollo de Modelos ALIA
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### Cite this model
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Please cite this model as:
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```
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@misc{carvalho_salamandra_instruct_2025,
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title = {Carvalho-Salamandra-Instruct: A Multilingual Instruction-Tuned Model for Underrepresented Languages},
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author = {Proxecto Nós Team},
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year = {2025},
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publisher = {HuggingFace},
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howpublished = {\url{https://huggingface.co/proxectonos/Carvalho-Salamandra-Instruct}},
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}
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```
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config.json
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"LlamaForCausalLM"
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 11008,
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"max_position_embeddings": 8192,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pad_token_id": 6,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.51.3",
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"use_cache": false,
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"vocab_size": 256000
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}
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"repetition_penalty": 1.2,
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"temperature": 0.6,
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"transformers_version": "4.51.3"
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"model.layers.7.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.9.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.norm.weight": "model-00003-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
34
special_tokens_map.json
Normal file
34
special_tokens_map.json
Normal file
@@ -0,0 +1,34 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>"
|
||||
],
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|reserved_token_1|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:990527d1e7b98c027d386c742250b2f8517bd3adf98c46cc6c1c2f35b234c224
|
||||
size 37007559
|
||||
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
1105
tokenizer_config.json
Normal file
1105
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user