T1 S10 Allam7b LoRA Prompt
3-class Arabic text classifier over (text, target) pairs, formulated as a prompted sequence-classification head on top of a LoRA-adapted instruction-tuned LLM. Access to the model weights requires manual approval...
Fonte do modelo
- Tipo
- LoRA
- Tamanho do arquivo
- 153 MB
- Modelo base
- humain-ai/ALLaM-7B-Instruct-preview
- Versão
- vFP32
- Atualizado
- 31 de out. de 2026
- Downloads
- 5
- Fonte
- Hugging Face
Descrição da fonte
Arabic Text-Target Classifier (LoRA) — t1_s10_allam7b_lora_prompt
3-class Arabic text classifier over (text, target) pairs, formulated as a prompted sequence-classification head on top of a LoRA-adapted instruction-tuned LLM. Access to the model weights requires manual approval from the repository owner.
Base model
humain-ai/ALLaM-7B-Instruct-preview
Labels
LABEL_0LABEL_1LABEL_2
Usage
from transformers import AutoTokenizer, AutoModelForSequenceClassification
from peft import PeftModel
import torch
base_model_id = "humain-ai/ALLaM-7B-Instruct-preview"
adapter_id = "HassanB4/t1_s10_allam7b_lora_prompt"
tokenizer = AutoTokenizer.from_pretrained(adapter_id)
base_model = AutoModelForSequenceClassification.from_pretrained(base_model_id, num_labels=3)
model = PeftModel.from_pretrained(base_model, adapter_id)
model.eval()
text = "..."
target = "..."
prompt = f"{text} [SEP] {target}"
inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512)
with torch.no_grad():
logits = model(**inputs).logits
predicted_label = int(torch.argmax(logits, dim=-1)[0])
Fontes
1 fonte
Fontes
1 fonteVerificado 31 de out.
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Artefatos de modelo
1 artefato
Artefatos de modelo
1 artefatoadapter_model.safetensors
safetensors · FP32 (unverified) · 153 MB · SHA-256 b969247a72af…993e · Hugging Face
Download fileTrechos de fonte
3 trechos
Trechos de fonte
3 trechos--- language: ar license: mit library_name: peft base_model: humain-ai/ALLaM-7B-Instruct-preview tags: - arabic - text-classification - lora --- # Arabic Text-Target Classifier (LoRA) — t1_s10_allam7b_lora_prompt 3-class Arabic text classifier over (text, target) pairs, formulated as a prompted sequence-classification head on top of a LoRA-adapted instruction-tuned LLM. Access to the model weights requires manual approval from the repository owner. ## Base model `humain-ai/ALLaM-7B-Instruct-preview` ## Labels - `LABEL_0` - `LABEL_1` - `LABEL_2` ## Usage ```python from transformers import AutoTokenizer, AutoModelForSequenceClassification from peft import PeftModel import torch base_model_id = "humain-ai/ALLaM-7B-Instruct-preview" adapter_id = "HassanB4/t1_s10_allam7b_lora_prompt" tokenizer = AutoTokenizer.from_pretrained(adapter_id) base_model = AutoModelForSequenceClassification.from_pretrained(base_model_id, num_labels=3) model = PeftModel.from_pretrained(base_model, adapter_id) model.eval() text = "..." target = "..." prompt = f"{text} [SEP] {target}" inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512) with torch.no_grad(): logits = model(**inputs).logits predicted_label = int(torch.argmax(logits, dim=-1)[0]) ```
Source context: 5 downloads · 0 likes · Pipeline text-classification · Library peft · Repo HassanB4/t1_s10_allam7b_lora_prompt
Source context: 7 downloads · 0 likes · Pipeline text-classification · Library peft · Repo HassanB4/t1_s10_allam7b_lora_prompt
