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+
+---
+
+license: apache-2.0
+base_model: mistralai/Mistral-7B-v0.3
+tags:
+- generated_from_trainer
+model-index:
+- name: home/migel/tess-2.5-mistral-7B-phase-1
+  results: []
+
+---
+
+![](https://cdn.discordapp.com/attachments/791342238541152306/1264099835221381251/image.png?ex=669ca436&is=669b52b6&hm=129f56187c31e1ed22cbd1bcdbc677a2baeea5090761d2f1a458c8b1ec7cca4b&)
+
+# QuantFactory/Tess-3-7B-SFT-GGUF
+This is quantized version of [migtissera/Tess-3-7B-SFT](https://huggingface.co/migtissera/Tess-3-7B-SFT) created using llama.cpp
+
+# Original Model Card
+
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.4.1`
+```yaml
+base_model: mistralai/Mistral-7B-v0.3
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+tokenizer_use_fast: false
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+model_config:
+
+datasets:
+  - path: /home/migel/ai_datasets/tess-v1.5b-chatml.jsonl
+    type: sharegpt
+    conversation: chatml
+  - path: /home/migel/ai_datasets/Tess-3.0/Tess-3.0-multi_turn_chatml.jsonl
+    type: sharegpt
+    conversation: chatml
+  - path: /home/migel/ai_datasets/Tess-3.0/Tess-3.0-single_turn_chatml.jsonl
+    type: sharegpt
+    conversation: chatml
+
+chat_template: chatml
+
+dataset_prepared_path: last_run_prepared_mistral
+val_set_size: 0.0
+output_dir: /home/migel/tess-2.5-mistral-7B-phase-1
+
+resume_from_checkpoint: /home/migel/tess-2.5-mistral-7B-phase-1/checkpoint-440 
+auto_resume_from_checkpoints: true
+
+sequence_len: 16384
+sample_packing: true
+pad_to_sequence_len: true
+
+gradient_accumulation_steps: 4
+micro_batch_size: 4
+num_epochs: 1
+logging_steps: 1
+optimizer: adamw_8bit
+lr_scheduler: constant
+learning_rate: 1e-6
+
+wandb_project: mistral-7b
+wandb_watch:
+wandb_run_id:
+wandb_log_model:
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+
+gradient_checkpointing: true
+gradient_checkpointing_kwargs:
+  use_reentrant: false
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+saves_per_epoch: 10
+evals_per_epoch: 10
+save_total_limit: 3
+save_steps:
+eval_sample_packing: false
+debug:
+deepspeed: /home/migel/axolotl/deepspeed_configs/zero3_bf16.json
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+  bos_token: "<|im_start|>"
+  eos_token: "<|im_end|>"
+  pad_token: "<|end_of_text|>"
+
+
+```
+
+</details><br>
+
+# Tess-3-7B-SFT
+
+![Tess-3](https://huggingface.co/migtissera/Tess-v2.5-Qwen2-72B/resolve/main/Tess-v2.5.png)
+
+Tess-3-7B is a finetuned version of the Mistral-7B-v0.3 base model. This version is the first phase of the final Tess-3 model, and have been trained with supervised fine-tuning (SFT) on a curated dataset of ~500K samples. The total SFT dataset contains about 1B tokens.
+
+This model has 32K context length. 
+
+
+# Sample code to run inference
+
+Note that this model uses ChatML prompt format.
+
+```python
+import torch, json
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from stop_word import StopWordCriteria
+
+model_path = "migtissera/Tess-3-7B-SFT"
+output_file_path = "/home/migel/conversations.jsonl"
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_path,
+    torch_dtype=torch.float16,
+    device_map="auto",
+    load_in_4bit=False,
+    trust_remote_code=True,
+)
+
+tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
+
+terminators = [
+    tokenizer.convert_tokens_to_ids("<|im_end|>")
+]
+
+def generate_text(instruction):
+    tokens = tokenizer.encode(instruction)
+    tokens = torch.LongTensor(tokens).unsqueeze(0)
+    tokens = tokens.to("cuda")
+
+    instance = {
+        "input_ids": tokens,
+        "top_p": 1.0,
+        "temperature": 0.75,
+        "generate_len": 1024,
+        "top_k": 50,
+    }
+
+    length = len(tokens[0])
+    with torch.no_grad():
+        rest = model.generate(
+            input_ids=tokens,
+            max_length=length + instance["generate_len"],
+            use_cache=True,
+            do_sample=True,
+            top_p=instance["top_p"],
+            temperature=instance["temperature"],
+            top_k=instance["top_k"],
+            num_return_sequences=1,
+            pad_token_id=tokenizer.eos_token_id,
+            eos_token_id=terminators,
+        )
+    output = rest[0][length:]
+    string = tokenizer.decode(output, skip_special_tokens=True)
+    return f"{string}"
+
+conversation = f"""<|im_start|>system\nYou are Tesoro, a helful AI assitant. You always provide detailed answers without hesitation.<|im_end|>\n<|im_start|>user\n"""
+
+while True:
+    user_input = input("You: ")
+    llm_prompt = f"{conversation}{user_input}<|im_end|>\n<|im_start|>assistant\n"
+    answer = generate_text(llm_prompt)
+    print(answer)
+    conversation = f"{llm_prompt}{answer}\n"
+    json_data = {"prompt": user_input, "answer": answer}
+
+    with open(output_file_path, "a") as output_file:
+        output_file.write(json.dumps(json_data) + "\n")
+```
+
+# Join My General AI Discord (NeuroLattice):
+https://discord.gg/Hz6GrwGFKD
+
+# Limitations & Biases:
+
+While this model aims for accuracy, it can occasionally produce inaccurate or misleading results. 
+
+Despite diligent efforts in refining the pretraining data, there remains a possibility for the generation of inappropriate, biased, or offensive content. 
+
+Exercise caution and cross-check information when necessary. This is an uncensored model.