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Model: mrshu/mistral-sk-7b-alpaca-slovak-it 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: apache-2.0
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language:
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- sk
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- en
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base_model:
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- slovak-nlp/mistral-sk-7b
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datasets:
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- saillab/alpaca-slovak-cleaned
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tags:
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- slovak
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- instruction-tuned
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- mistral
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- lora
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- merged-lora
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- text-generation
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pipeline_tag: text-generation
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---
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# Mistral-sk-7B Alpaca Slovak IT
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Mistral-sk-7B Alpaca Slovak IT is an instruction-tuned Slovak assistant model
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derived from `slovak-nlp/mistral-sk-7b`. It was trained with a LoRA supervised
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fine-tuning recipe on Slovak Alpaca-style instruction data and then merged back
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into the base model, so the released artifact can be loaded directly with
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`transformers`.
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This is the compact 7B release candidate. It is intended for Slovak assistant
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experiments where lower memory use is more important than using the strongest
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available model in this release set.
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## Intended Use
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This model is intended for Slovak instruction following, Slovak question
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answering, drafting, rewriting, summarization-style prompts, and general
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assistant workflows where Slovak is the primary language.
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It can also respond to English prompts and translation-style requests, but
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language control is weaker than in larger models. Use additional
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application-level checks for strict formatting, policy compliance, or
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high-reliability translation.
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Do not use this model as the sole source for medical, legal, financial, safety,
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or other high-stakes decisions. It has not been safety aligned, red-teamed, or
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moderated for production deployment.
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## Model Details
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| Field | Value |
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| --- | --- |
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| Base model | `slovak-nlp/mistral-sk-7b` |
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| Base revision | `089497ae0d72018e9591895c54f774bf0b4a83a4` |
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| Release repository | [`mrshu/mistral-sk-7b-alpaca-slovak-it`](https://huggingface.co/mrshu/mistral-sk-7b-alpaca-slovak-it) |
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| Architecture | Mistral causal language model |
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| Tuned artifact | Merged full-weight checkpoint |
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| Adapter used during training | LoRA |
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| Weight dtype | bfloat16 |
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| License | Apache-2.0 |
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## Training Data
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The model was instruction-tuned on
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[`saillab/alpaca-slovak-cleaned`](https://huggingface.co/datasets/saillab/alpaca-slovak-cleaned),
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a Slovak Alpaca-style instruction dataset.
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Dataset preparation converted each example into a chat-style conversation with
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system, user, and assistant messages. Empty instruction/output examples were
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excluded, and duplicate instruction/input/output triples were removed across
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the prepared splits.
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| Split | Rows |
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| --- | ---: |
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| Train | 41,601 |
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| Held-out | 10,401 |
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The data preparation used dataset revision
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`058172466eb1d6a28b161f29c74350911d154161`.
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Each training conversation used this system prompt:
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```text
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Si užitočný asistent. Riaď sa jazykom a požadovaným formátom používateľa. Ak používateľ nežiada iný jazyk, odpovedaj po slovensky.
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```
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## Training Recipe
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The model was trained with supervised fine-tuning using PEFT LoRA. Only the
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assistant turns were included in the training loss.
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| Setting | Value |
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| --- | --- |
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| LoRA rank / alpha / dropout | `32` / `64` / `0.05` |
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| Target modules | linear projection modules |
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| Sequence length | `4096` |
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| Sample packing | enabled |
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| Epochs | `1` |
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| Effective batch size | `16` |
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| Micro batch size | `2` |
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| Gradient accumulation | `8` |
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| Learning rate | `1e-4` |
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| Scheduler | cosine |
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| Warmup ratio | `0.06` |
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| Optimizer | fused AdamW |
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| Precision | bfloat16 |
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| Gradient checkpointing | enabled |
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| Seed | `42` |
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After training, the LoRA adapter was merged into the base model with PEFT and
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saved as a standalone safetensors checkpoint with a Mistral chat template in
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the tokenizer.
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## Usage
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_id = "mrshu/mistral-sk-7b-alpaca-slovak-it"
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tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.bfloat16,
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device_map="auto",
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trust_remote_code=True,
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)
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messages = [
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{
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"role": "system",
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"content": (
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"Si užitočný asistent. Riaď sa jazykom a požadovaným formátom "
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"používateľa. Ak používateľ nežiada iný jazyk, odpovedaj po slovensky."
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),
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},
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{"role": "user", "content": "Stručne vysvetli, čo je LoRA."},
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]
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inputs = tokenizer.apply_chat_template(
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messages,
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add_generation_prompt=True,
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return_tensors="pt",
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).to(model.device)
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outputs = model.generate(
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inputs,
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max_new_tokens=512,
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do_sample=True,
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temperature=0.7,
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top_p=0.95,
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)
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print(tokenizer.decode(outputs[0][inputs.shape[-1]:], skip_special_tokens=True))
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```
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## Limitations
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- The supervised fine-tuning data is translated instruction data, so the model
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may inherit translation artifacts, unnatural phrasing, or source-dataset
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biases.
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- The model is strongly biased toward Slovak responses. Explicit English-only
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or strict-format requests may not be followed reliably.
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- Strict JSON, exact labels, citations, and other constrained formats should be
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validated outside the model.
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- The model may hallucinate facts, produce unsafe content, or follow malicious
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instructions without additional safeguards.
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chat_template.jinja
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{{ bos_token }}{%- set ns = namespace(system='') -%}{%- for message in messages -%}{%- if message['role'] == 'system' -%}{%- set ns.system = message['content'] -%}{%- elif message['role'] == 'user' -%}{{ '[INST] ' + (ns.system + '\n\n' if ns.system else '') + message['content'] + ' [/INST]' }}{%- elif message['role'] == 'assistant' -%}{{ ' ' + message['content'] + eos_token }}{%- endif -%}{%- endfor -%}{%- if add_generation_prompt -%}{{ ' ' }}{%- endif -%}
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config.json
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{
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"dtype": "bfloat16",
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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": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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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": 2,
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"rms_norm_eps": 1e-05,
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"rope_parameters": {
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"rope_theta": 10000.0,
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"rope_type": "default"
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},
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"transformers_version": "5.5.0",
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"use_cache": true,
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"vocab_size": 32000
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}
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"transformers_version": "5.5.0"
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}
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}
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||||
}
|
||||
268053
tokenizer.json
Normal file
268053
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
17
tokenizer_config.json
Normal file
17
tokenizer_config.json
Normal file
@@ -0,0 +1,17 @@
|
||||
{
|
||||
"add_prefix_space": true,
|
||||
"backend": "tokenizers",
|
||||
"bos_token": "<s>",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"extra_special_tokens": [],
|
||||
"is_local": true,
|
||||
"legacy": true,
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": "</s>",
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "TokenizersBackend",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user